Bias in hiring didn’t begin with AI. It’s been with us in job descriptions, résumé screens, and interviews for decades. The useful thing AI gives us isn’t perfection; it’s measurement. Done right, AI makes decisions easier to audit, explain, and improve. That’s the bar we set at Tezi.

What Tezi’s AI agents do (and don’t)

Tezi’s AI agents review every inbound applicant according to the employer’s predefined criteria, run a short structured screen (eligibility, location, timing, compensation, etc.), answer candidate questions, and produce transparent, job-related recommendations for the hiring team. Then, the handoff matters: our agents do not make advance/reject decisions. They recommend; people decide. That’s both how we’ve built the product and how I’ve described it publicly. (youtube.com)

The agents are blind by design to protected-class information (e.g., gender, race, ethnicity, profile photos, names). We intentionally engineer away inputs that shouldn’t influence a hiring outcome and focus on evidence tied to a candidate’s track record and skills.

Why “fairness through unawareness”

We chose a blind approach because candidates find it fair and straightforward. In a recent study, people rated hiring algorithms fairest when they didn’t use demographic attributes, and they viewed companies using that approach more positively – making them more willing to apply. This doesn’t mean Tezi ignores outcomes. It means we start with a process that is understandable to candidates and then measure the results carefully.

A fair system can explain itself

A fair hiring system should show its work: which signals mattered, how they were weighed, and why a recommendation was made. Tezi’s AI agents log the job-related evidence behind every recommendation, allowing recruiters and hiring managers to examine the rationale.

By contrast, human decision-making is powerful but not always transparent – even to ourselves. Two recent strands of evidence matter:

• Unstructured interviews can seem convincing but may compromise accuracy. Research in Judgment and Decision Making shows we often “make sense” of conversational details that dilute predictive signal, raising confidence while lowering validity. That’s hard to audit after the fact.

• Bias appears under pressure. A recent paper found participants were ~30 percentage points more likely to hire workers perceived as White vs. Black, and time pressure amplified discriminatory choices (exactly the environment of rushed résumé screens).

When we pair structured, logged AI recommendations with human judgment, we achieve the best of both: consistency and explainability upfront, along with accountability and context at the decision point.

Evidence that the baseline isn’t fair

Large-scale studies continue to show discrimination in hiring:

• A PNAS 26-year-long meta-analysis of U.S. field experiments (1989–2015) found no decline in discrimination against Black applicants over time. The human baseline has problems we can’t wish away.

• An employer-level experiment summarized by the University of Chicago’s Becker Friedman Institute graded big firms: the worst-graded favored White over Black applicants by ~24%; the best still showed a smaller but measurable gap.

This is why we focus on design choices (blind inputs, structured screens) and ongoing audits.

Audits, not assurances: what we measure and publish

Our collaboration with Warden AI on The State of AI Bias in Talent Acquisition 2025 echoes what we see internally:

• AI vs. human fairness: Warden’s industry data shows AI averages 0.94 on fairness metrics compared to 0.67 for human-only processes, and AI can be up to 45% fairer for women and racial-minority candidates when implemented responsibly.

• Independent audit: We’ve undergone an external audit under New York City’s Local Law 144, Colorado SB 205, California FEHA, and EU AI Act (Regulation 2024/1689). On the audited use cases (application review & chat screening), Tezi’s system showed no measured bias across any of the eighteen protected class demographics – consistent with how we design and validate. See the details on our AI Audit Center.

• Continuous monitoring: We onboarded Warden AI to automatically test our AI agents across eighteen protected-class dimensions every month. Continuous monitoring matters because our product evolves quickly, laws change, and data drifts; recurring audits create a correction loop instead of a one-time certificate.

Put simply, we prefer proof over promises, and we instrument the system so we can continually prove it.

Anti-bias efforts matter for legally compliant hiring

New York City, Colorado, and California are the most consequential U.S. jurisdictions with AI-specific rules touching hiring today:

• New York City (Local Law 144): If you use an automated employment decision tool in NYC, you must complete an independent bias audit, publish a summary of results, and give advance notice to candidates. Screening use counts – not just final decisions.

• Colorado (SB24-205): The first statewide law covering “high-risk” AI systems, including employment decisions. It imposes duties on developers (Tezi) and deployers (employers) for risk management, impact assessments, monitoring, and reporting, with enforcement under the Consumer Protection Act.

• California (FEHA ADS Regulations). Effective October 1, 2025, California’s Civil Rights Council finalized rules under FEHA that expressly regulate Automated-Decision Systems (ADS) in employment. They prohibit discriminatory use of ADS or selection criteria, and expand documentation, record-keeping, and accommodation duties – creating one of the most comprehensive state frameworks for AI in hiring.

Designing to these standards – and monitoring continuously – means we’re not just compliant in one jurisdiction; we’re building durable governance for how AI is used in hiring.

What we commit to

• Blind by default. Tezi’s agents exclude protected-class inputs and obvious proxies where possible.

• Human in the loop. Agents recommend; people decide.

• Explainable outputs. Every recommendation includes the job-related evidence and rationale.

• Independent, ongoing audits. 3rd-party audits every month across eighteen protected classes.

• Regulatory compliance. We designed Tezi to reduce bias from the onset, which enabled us to meet the NYC, CO, and CA requirements with ease.

The outcome we’re after

Better hiring isn’t only about quality and speed; it’s also about trust. Candidates engage when they know they’ll be evaluated on job-related merit. Recruiters and hiring managers make stronger decisions when they can see the reasoning, compare it across groups, and course-correct with data.

That’s why we design Tezi’s AI agents to be explainable, audited, and accountable – and why we measure fairness as an ongoing practice, not a one-time claim.

If you want to see how this works on your roles – especially if you’re sitting on an overwhelming pile of applications – get in touch. Our team would love to give you a demo.

Over the past few months, we’ve hosted conversations with TA leaders across the country — through dinner gatherings, networking happy hours, and thought-provoking panel discussions — all centered on how AI is reshaping the recruiting landscape. And while technology continues to accelerate, one theme consistently emerges: the heart of talent acquisition remains profoundly human.

Recapping the learnings and shared insights from Talent Acquisition (TA) and People leaders across these events – featuring leaders from companies like Airbnb, Snowflake, Toast, Fastly, and Centivo, we dove deep into the current and future state of AI in TA — and how leaders are preparing their teams for what’s next.

1. The recruiter role is evolving.

AI is here — and it’s transforming how Talent Acquisition teams operate.

As automation takes over the higher-volume, lower-EQ tasks like sourcing, scheduling, and screening, TA leaders are reimagining what meaningful career growth looks like in this new era. There’s broad consensus that AI won’t replace recruiters — but recruiters who don’t adapt their workflows risk being left behind.

Instead of eliminating roles, AI is reshaping them. The next generation of recruiters will spend less time on administrative tasks and more time on strategy, influence, and storytelling. The recruiter of tomorrow is part marketer, part operator, and part talent strategist — using AI to amplify their impact rather than diminish it.

2. Keeping recruiting human is essential.

Despite the influx of tools and automation, everyone agreed that recruiting’s competitive edge remains human connection.

As one leader put it, “Being a great host might just be the most important skill a recruiter can develop.” It’s about creating a thoughtful, personal candidate experience — the kind that leaves people feeling seen, not processed.

3. Reskilling for relevance is likely.

TA practitioners aren’t waiting for the future to arrive — they’re already reskilling.

Leaders are upskilling their teams in data fluency, employer branding, and talent analytics. The throughline: AI won’t make recruiters obsolete; it will make them more insight-driven and consultative.

4. Responsible AI and ethical guardrails are an absolute necessity.

As AI becomes more deeply embedded in the recruiting process, TA leaders are increasingly focused on how to deploy it responsibly.

The conversation is shifting from “Can we use AI?” to “How should we?” Leaders are establishing ethical frameworks to ensure fairness, transparency, and compliance — from mitigating bias in sourcing algorithms to maintaining candidate privacy and consent. Those who balance innovation with integrity are emerging as the trusted voices shaping the next era of talent acquisition.

5. AI is redefining the candidate experience.

While automation promises speed and efficiency, the challenge ahead is designing experiences that remain personal and authentic.

Leaders are experimenting with AI-driven personalization — chatbots that feel human, outreach that’s data-informed yet empathetic, and always-on support available around the clock that offers genuine connection, even when no one’s technically “on.”

The goal isn’t to remove humans from the process, but to enhance human connection at scale, ensuring candidates feel valued throughout their tech-powered journey.

What’s Next?

These conversations are energizing reminders that while AI is transforming how we work, it’s also elevating what it means to lead. We’ll continue bringing TA leaders together to share, debate, and learn — because the best ideas emerge from real conversation.

If you’d like to join an upcoming session (or help us bring one to your city), email newsletter@tezi.ai. Let’s make it happen in 2026!

Hiring is magical when it works well. It is a thrill for a candidate to find their dream job or for a hiring manager to find that amazing hire they can’t wait to start on their team. But the process to get there is often slow and expensive, with a lot of tedious, repetitive work that takes up countless hours.

and I started Tezi with a vision to create a product that takes the tedium out of recruiting so hiring teams can focus on what they do best and enjoy the most: meeting with amazing candidates and selling the vision, evaluating mutual fit and closing the deal. We built Max, an autonomous AI agent that can partner with hiring teams across the recruiting funnel: building a sourcing list, sending out email sequences, reviewing thousands of resumes to find the gems, screening candidates or scheduling interviews.

Since Max works across the recruiting workflow from opening a role to offer, no matter what your pain point is, Max can very likely help. Whether you are a founder or hiring manager at a small startup or a recruiter at a larger company, Max can take the tedious, repetitive tasks in recruiting off your plate.

While AI has tremendous potential for shaping the future of work, it is nascent technology. A customer recently told us: “I’ve tried several AI recruiting tools and yours is the only one that actually works.” How did we get there?

• We painstaking tuned the AI and built surrounding technology and software so Max can work consistently and be reliable and predictable.

• We leveraged the knowledge, experience, and skill of amazing recruiters on our team and in our network who helped Max get good at not only the science of recruiting but also the art, be it in crafting the ideal message to spark a passive candidate’s interest or a web chat screen that feels natural and informative.

• We designed Max knowing that at its core, recruiting is innately human - after all, it is one human deciding to work with a group of other humans. Our goal was to take on all the meticulous work that leads to facilitating the best human interactions.

Here are some stats about Max in the few months since our initial launch:

• Used by dozens of customers for nearly a hundred job roles.

• Recruited globally across a variety of functions including engineering, AI, sales, marketing, operations, customer success, product, and more.

• Sourced tens of thousands of high quality candidates and reviewed just as many inbound applications.

• Screened and scheduled interviews for over a thousand candidates.

Ultimately, across all Max’s functionality, we estimate that we saved our customers over 10,000 recruiting hours in just the last few months.

While I would love to tell you a lot more about the magic Max brings to our customers, what is even better is hearing directly from them:

“The way we search for talent has long been tangled in inefficiency, drowning in excess, and blind to what truly matters. Max moves through this chaos with clarity. It knows where to look, whom to engage, and how to cut through the noise to bring forth those who belong. It is not just technology; it is a shift in understanding, a way forward.

I’ve seen a lot of tools that promise to make hiring easier, but Max actually delivers. It got up and running with barely any setup, dialed in on the right candidate profiles, sourced thousands of top-quality applicants, and took care of scheduling like clockwork. On top of that, it filtered out the noise from our inbound pipeline, so we only spent time on the best. This is the future of recruiting - no doubt about it.” - Mawulom Nenonene, Head of Talent Acquisition at Point

“Max replaced our need to source at all for some roles. By reviewing our overwhelming backlog of inbound applicants and advancing only the best ones, Max found 29 strong candidates for a recent role. We closed a great hire in a little more than one month from opening the role. I'm very pleased with Max!” - Mackenzie Tuller, Head of Operations at Mutiny

“The calibration process with Max is a treat. Even with a descriptive job description in place, Max made me refine the key attributes that we were looking for in the role through a series of selections/rejections from a candidate pool. The magic happened at the end of the process. After a couple of weeks, some candidates started engaging with Max and I was pleasantly surprised when I talked to some of them including AI engineers. They were not aware that an AI agent was reaching out to them! With the volume of well-targeted outreach Max is sending and the resulting interest, we have a real shot at filling our roles faster.” - Santhosh Srinivasan, VP of Engineering at Acryl Data

"While Max does require some ongoing human oversight, it excels at capturing our nuanced target candidate profile. By automating sourcing and screening across thousands of candidates, Max has become an excellent complement to our traditional recruiting practices, especially during high growth hiring sprints.” - Aniruddha Laud, Head of Engineering at Pocus

When candidates interact with Max, they tend to love it. Max is online 24/7 and responds instantly to inquiries at any time of day or night. Rather than wait for days for a recruiter screen, candidates can chat with Max instantly at any time they choose.

“Initially, I was hesitant about the process, but I was pleasantly surprised by how well it worked. The flow was smooth and led naturally into the next question.” - Design candidate

“This is the first time I've received cold outreach from an AI recruiter and completed the screening. The entire experience was incredible. Natural, inclusive, efficient: I appreciated the conversational nature and time to craft solid answers.” - Marketing candidate

Max is ready for companies of all sizes and stages. If you don’t have any investment in recruiting software, Max can work standalone and be your one-stop solution. If you have an ATS, Max can seamlessly sync its activity so you can leverage it without having to leave the ATS interface. We are compliant with leading standards like SOC2 (security), CCPA (data privacy) and NYC 144 (AI & employment regulations).

If you’d like to experience the future of recruiting with Max, get in touch!

It’s a big day for us at Tezi! We’ve raised $9M in seed funding led by 8VC and Audacious Ventures, with support from Liquid 2, Afore, Prime Set, and South Park Commons. Angel investors in the round include the founding CEOs of Instacart and Thumbtack. 

The best companies are built by the best teams, which require the best recruiters working behind the scenes. Traditionally, companies need to hire teams of recruiters when business is good, a high-commitment and inflexible solution that often leads to layoffs when hiring slows, or hire an agency, where incentives are often misaligned. Both options can be prohibitively expensive. On average, companies in the US spend $4,700 per hire, with costs skyrocketing to $20,000-$40,000 for STEM positions. In addition to cost, hiring can be slow to bootstrap, often taking weeks to get an agency or recruiter in place, and the quality can be hit or miss.

That is, until now. Max is the first autonomous AI employee trained by top hiring managers and recruiters to lead the end-to-end recruiting process, including: 

• Sourcing with natural language search, 750M candidate profiles globally, deep calibration, and personalized emails 

• Screening to rank inbound applications, decision them, and assess & sell the best applicants. 

• Scheduling that gracefully handles complex interview plans, last-minute reschedules, and interviewer bandwidth challenges. 

Max uses natural language that you can interact with where you already work, on Slack, or the web. Just like a helpful coworker, it can nudge you and answer your follow-up questions. Setup the role once and Max does all the work autonomously, keeping you informed along the way, and interviews start to appear on your calendar within days.

Companies relying on Max see the following benefits:

• Ramp-up time with AI is reduced from weeks to minutes, which speeds up the time-to-hire dramatically and delivers business impact faster.  

• Consistent and high quality candidate experience with AI. Max is available to chat with candidates at any time of their choosing, responds instantaneously, and never drops the ball.

• Lower costs associated with AI recruitment allow businesses to reinvest more funds into R&D, Sales, and Marketing.

• With AI’s flexible capacity, hiring can scale up or down instantly, meeting the needs of the business or market cycles.

• Reduced bias and higher consistency in decisioning aided by an expertly trained AI.

Tezi allows your employees to focus on more strategic recruiting activities that require a human touch, like evaluating candidates, selling them on the role, and closing the hire. Over time, Max will continue to gain more capabilities and streamline more of the workflow of recruiting including interviewing assistance, processing offers and seamlessly transitioning hires to onboarding.   

Under the covers, Max uses agentic AI technology powered by dozens of specialized agents, each trained to do one recruiting task very well, seamlessly orchestrated to deliver the experience of interacting with one AI recruiter.

I met my cofounder, Jason James, while at Thumbtack where I was CTO and he was VP of Product and Design. We’ve each been in management and executive roles for over a decade across premier technology companies, between us having hired over 500 people. We became intimately familiar with building out teams, as well as the many obstacles that come with finding and hiring the right people and knew we had to find a better solution.

While we’re still in our early days, tech companies are already seeing the power of what’s possible with Tezi. Whether it is a small company, strapped for time and looking to have Max run all their open roles, or a larger company looking to drive efficiency by augmenting capacity to an existing recruiting team, Max can be a great option. With Tezi, recruiting capacity will never be a bottleneck to hiring as fast as the company desires. Democratizing access to a high-quality recruiting partner for every hiring manager around the globe levels the playing field in finding and recruiting excellent talent.

And finally, here’s what our investors had to say about our news:

“Talent and recruiting have remained the dark arts of the enterprise: a near-infinite market that has not seen any true technological advancement in a generation. Even with the inflection in AI, attacking this gap is not for the faint of heart. It requires an exceptional founding team, not just technically, but in all the complexities and nuances of the domain. At 8VC, we are exhilarated to have found such a team in Tezi. RVP (who I failed to recruit many times in a past life, but became a friend!) and Jason have each spent 22 years perfecting their craft, together hiring 500+ world-class talents in engineering, product and design. We look forward to RVP and Jason transforming this space with their trademark virtuosity.” 

– Bhaskar Ghosh, Partner, 8VC

“Recruiting A+ talent has always been one of the most important imperatives at the best-in-class companies. But before Tezi, software efforts in recruiting have been to provide tooling to make recruiters marginally more efficient. Tezi is the first recruiting AI agent that autonomously runs the recruiting workflow end to end, from sourcing the *best* talent out there, to screening applicants and scheduling interviews, with a friction-free process leading to a high quality candidate experience. Tezi makes recruiting a strategic edge for its customers. That's huge!" 

– Nakul Mandan, Founder & Partner, Audacious Ventures

If you’re excited about what we’re building, interested in learning more, or want to try out Max at your company, visit tezi.ai.

After more than a decade of digital product design, it’s been refreshing and a totally new experience creating an AI agent (Max, Tezi’s autonomous AI recruiter). Many old design paradigms became irrelevant quickly, and new ways of working emerged. Here’s what I’m seeing five months into agentic AI design:

1. Content is the Canvas, Not UI

The user interface (UI) is the final deliverable in traditional product design. Designers craft every pixel. However, when designing AI agents, the content itself is the canvas. The focus shifts from how information is presented to the substance and relevance of the content delivered by the AI. My recent design deliverables could’ve just been plaintext docs. When crafting an active AI collaborator that interacts proactively with humans, the communication itself is the user interface.

2. Directional, Not Pixel-Perfect

Traditional product design often demands pixel-perfect precision, where every element is carefully placed and aligned. There’s one right way for a screen to be. In contrast, agentic AI design is more directional or gestural. “I’d like the agent to hit these three key beats in the conversation and transition out of it like this…” Like working with humans, you get better results by allowing it to improvise and avoiding prescriptive and limiting constraints.

3. Dogfooding is Designing

Dogfooding, or using your own product, is of new importance in agentic AI design. Since you truly don’t know what the AI will do, you have to “f*ck around & find out.” When using the product, you figure out what’s not working and keep designing with your engineering partners. If QA was normally the last 10%, consider it now the last 50%.

4. Expert Defaults

A user’s initial interactions with your agent will set the standard for how intelligent, capable, and useful they believe it to be. In our case, you shouldn’t have to teach a recruiter how to recruit. An expert recruiter comes with decades of experience and knows all the best practices. You can ask them to work a little differently to suit your company and your unique needs, but the defaults are pretty damn good. That’s an absolute must in this new era of AI agents. It’s ultimately why the vanilla, catch-all, thin wrapper agentic products aren’t getting traction. It’s too much work to make them useful.

5. AI Agents are Better and Worse than Humans

Part of agentic design is to leverage what the agent will absolutely be better at than humans while failing gracefully and transparently in the areas where humans are still better. For our product, a human just can’t tear through 3,000 resumes in seconds and tell you who the top 10 applicants are, but AI can. However, no one will join a company because the AI agent is so compelling; we need humans to establish that connection and rapport with candidates. A quality agentic product will know where it’s great and where it falls down.

6. Leverage Familiar (Human) Paradigms

Grounding the agent in familiar human paradigms helps bridge the gap between the old and the new. This approach reduces the learning curve and fosters greater acceptance, trust, and ease of use. In our case, that meant building for conversations in Slack. Any hiring manager is very familiar with Slacking their recruiting partner to make decisions about candidates, check in on the pipeline, and relay referrals. An ideal agentic product will leverage the patterns for human-to-human interactions to take a shortcut to successful human-to-AI interactions.

In the two months since we incorporated Tezi (in stealth mode), we’ve hired a lot of tools and vendors to support us. Turns out starting from zero means no systems or processes are in place yet. Sharing where we netted out on each selection and why…

Banking: Went with Mercury. Our concerns about SVB-style, regional bank issues were allayed by their Treasury solution. I’d had great experiences with their product for my LLC, so as long as they could protect our funds they were an easy winner on user experience.

Business Credit Card: We wanted every employee to have a corporate card. It’s so easy to drop ship a card to a new employee and manage their limits in Mercury. At 1.5% cashback, we didn’t feel the need to explore Ramp, Brex, etc.

Payroll, Health Benefits & HRIS: Evaluated Rippling, Gusto, and Deel. Went with Gusto because it was easier to get onboarded (no Sales gate), lower cost, and fewer à la carte add-on unexpected costs. We recognized we may need to migrate to something else later.

Expense Tracking: Gusto has a very basic expense management tool for reimbursing employees for any charges on their personal cards. Since we mostly use corporate cards via Mercury, this was good enough, so we didn’t thoroughly evaluate Xero, Expensify, Concur, etc. It’s nice that reimbursements happen automatically with payroll.

Law Firm: Evaluated three that came highly recommended. We went with Gunderson Dettmer, as they have deep expertise in working with startups, are agile enough to keep up, and were willing to defer a lot of early billing until post-fundraising. We’ve been very happy with them and would highly recommend to other founders.

Bookkeeping & Tax Prep: Evaluated Pilot vs Bench. Went with Pilot even though they’re more expensive because of their experience in accrual-based accounting (vs. cash-based) which is a requirement for VC equity rounds. Pilot had better reviews and switching off of Bench seemed inevitable by Series A at the latest.

Cap Table & Comp Data: Evaluated Carta vs Pulley. Went with Carta even though its more expensive. The add-on products for Comp Data and QSBS Advising for our employees tipped it in Carta’s favor. It’s nice to not have to add-in another tool like Pave. That much of our equity from prior companies was already in Carta certainly helped too.

Chat: Never explored something besides Slack. It’s the default. This was actually our first tool and probably the true beginning of the company well before incorporation.

Email & Calendar: Obviously Google Workspace. Didn’t seriously contemplate anything else. Tried Calendly for scheduling, but the new-ish Bookable Appointments feature in GCal nuked my need for Calendly. Tried Superhuman as an alternative front-end to Gmail. Learning a new way to work through email ended up being net slower, so I reverted back to Gmail.

Video Conferencing: No idea why we’d pay for Zoom when GMeets is included in our Google Workspace subscription, and they’re effectively the same product.

Docs & Wiki: We used Google Docs for awhile. The early engineers wanted Notion instead for it’s richer formatting and better handling of code snippets, tables, etc. Notion is working out nicely as it’s much, much easier to find docs there.

Presentations: Tried to make the pitch deck in Tome. Learning a new tool and trying to get the AI to produce something useful was too slow. Reverted back to Google Slides in Google Workspace.

Research: Throughout ideation and fundraising, ChatGPT and Crunchbase were the most useful tools for understanding markets, investors, and prior art. Bard (RIP) was a little helpful as well.

Naming: ChatGPT was incredibly helpful at generating 100s of names through various prompts. From the hundreds, we were able to dilligence our top 10 with web searches, Crunchbase, GoDaddy, and Gunderson Dettmer.

Project Management: None of us liked Jira from prior companies. Asana doesn’t quite work for engineers. Karri Saarinen, the Linear CEO’s podcast appearances have been really influential on our thinking, so we tried Linear since it’s a very like-minded company. It’s working out really well so far.

Design Tool: Obviously Figma lol. No clue what the alternative would be even.

Co-Working: We use WeWork. Not sure I’d recommend them. The Sales process is slow and a hassle, but the price is reasonable for a quality workspace for the 1 week every 6 that we meet in-person.

State Registrations: To be a multi-state distributed company, the amount of state govt registrations for tax, payroll, worker’s comp, etc. is thoroughly exhausting. We’ve tried CorpNet and SingleFile both to outsource this problem. Neither can do it independently. We’ll be converging on using just SingleFile since they’re a bit better experience-wise.

Corporate Insurance: Tried Vouch and Embroker. Embroker was ~40% less expensive and entirely self-serve with instant underwriting and approval. I got a quote and checked out in the same session. Will be using them for future corporate insurance needs.

401k: Evaluated Betterment, Guideline, and LearnVest. Went with Guideline. Pricing across all three was roughly comparable, as was the process. Guideline was slightly more self-serve, faster, and my co-founder had good experiences with them and their app at his last company.

Code Repository: Went with Github, somewhat by default, but also Github Co-Pilot is such a valuable sweetener that prevents us from really exploring the market of alternatives.

Password Management: Went with 1Password. Been such a long-time happy user as a consumer, I didn’t contemplate learning or using a competitor.

Cloud Hosting: Trying out providers based on their generous & free startup credits. We will likely have to make a call on a final cloud provider around the time we start storing customer data. GCP Sales team coordination was a total mess, but the credits are the most generous.

EA: Tried a few AI admins like Xembly, Ohai, Lindy. None really worked. I’d have to very narrowly scope a task for the agent, which ultimately made it not an EA really. At the EOD, it’s just faster to do it myself.

Business Phone Line: Google Voice is good enough for our stage of company. Once we get some real customer support volume, we will need to re-evaluate.

Brand Design Studio: We evaluated a short list of 3 that I knew from my network. Based on their work, the process they outlined, startup expertise, and speed, we went with Moniker SF. Excited to see the results in a few months!

Recruiting ATS: No vendors or tools onboarded at the moment, just network hiring so far. Evaluated many tools previously. Ashby, Gem, and Dover seem to be the most compelling “all-in-one” solutions we’ve come across.

E-Sign: Using DocSend, but it’s very pricey. Exploring switching to Gusto’s or Carta’s versions since they’re already bundled in.

My overall B2B SaaS takeaways are:

1. Switching costs of learning a new workflow are a meaningful, but not an insurmountable barrier

2. It’s great to be a default (i.e. Slack, Figma, Google Workspace)

3. Employees bring their priors from former jobs with them when making these decisions, so a positive reputation is a brand moat

4. All-in-one (i.e. Mercury, Gusto, Carta), even if some of the features are weak, is far more compelling than a basket of point solutions