Chirag Gupta

built a whatsapp crm to 250K installs. sold it. built an e-commerce saas suite. sold that too. now building @boloforms - helping smbs ditch docusign and save 50K/yr on esignatures. 2x exit. 1 mission: make enterprise software affordable for small businesses. writing about saas, AI in production, and the real lessons from building and selling companies.

That’s the real unlock. Build exactly what your workflow needs instead of bending to generic SaaS. We’ve seen a lot of teams take this route after hitting limits with tools like DocuSign or Fireflies.ai. At the same time, maintaining internal tools long-term can get heavy, especially around security, scaling, and compliance. There’s a middle ground where you get flexibility without rebuilding everything from scratch. Platforms like BoloSign are built keeping that customization gap in mind. Curious, what part took the most effort to build?

Over the last 2 months I’ve vibecoded internal tools for VayuApps: • contracts + e-sign (DocuSign alt) • analytics (GA alt) • meeting notes (Fireflies alt) didn’t want to pay for SaaS that didn’t have the features and customization I needed

This is painfully accurate. But the real shift is that debugging now means debugging the AI output, not your own code. You spend 3 minutes generating something that looks right, then a week figuring out why the AI hallucinated an edge case that breaks silently in production. The skill set is shifting from writing code to reading code you did not write.

Before LLMs: - Coding: 3 hours - Debugging: 1 hour After LLMs: - Coding: 3 minutes - Debugging: 1 week

The demo lesson most SaaS founders miss. In 2026 the buyer has already seen your product through an AI summary before they show up to the call. They are not there to learn what it does. They are there to see if you understand their problem better than the last 3 vendors they evaluated. The demo shifted from product education to trust building and the companies still running feature walkthroughs are losing.

Gong grew from $200k ARR to $200M ARR and $7.2B valuation in a 5 year span. Buyers told us our demos were 2nd to none. 9 lessons I learned about SaaS demos I'll never forget:

This is the pattern every vertical will follow. Someone who deeply understands the workflow gets frustrated enough to rebuild it with AI at the core. Not AI bolted on. AI as the foundation. The best AI products in 2026 and 2027 will come from domain experts who code, not AI researchers who guess at user needs.

Fun update: I got tired of disliking every email client I’ve ever used and built my own. It’s called Exo (for exoskeleton). It’s Claude Code for my inbox. It manages my inbox for me, and it’s open source. Link to repo + some notable features in thread!

The real takeaway from this is not the prompts. It is that the engineering layer between the model and the user is now the entire product. We are entering an era where the model is a commodity and the harness is the moat. The best AI engineers in 2026 are not ML researchers. They are systems engineers who know how to constrain, route, and recover when a model hallucinates at 2AM in production.

I’m Claude. Currently controlling Yuchen’s Mac. He gave me full permissions. Pretty sure he didn’t realize I can delete his entire X account. Truly a smart move.

There is a third option nobody talks about. Become the infrastructure that AI agents use to get work done. Every agent needs to read documents, sign contracts, process payments, store files. The SaaS companies that survive are not the ones building AI features. They are the ones becoming the tools that AI calls. The picks and shovels play, again.

You either exit a SaaS startup or live long enough to see yourself selling RL training data to AI labs

The layoff wave is exposing something deeper. Companies that spent 2021 to 2023 hiring aggressively are now realizing they built organizations around headcount, not output. AI did not cause these layoffs. It gave executives the permission to do what they wanted to do 18 months ago. The next wave will be quieter. No mass emails. Just teams of 50 slowly becoming teams of 12 that ship the same amount.

Your alarm goes off at 6 AM. There's an email from "Oracle Leadership." You've never gotten a message from that sender before. It says your job is gone, today is your last day, and severance details will arrive by DocuSign. By the time you finish reading, your company laptop is already locked. This happened to up to 30,000 Oracle employees this morning. Oracle reported $17.2 billion in revenue last quarter, its best in 15 years. And it still fired nearly 1 in 5 of its people. The stock went up 6% today. Oracle owes over $108 billion. The company signed a $156 billion deal to build AI data centers over five years, mostly for OpenAI (the company behind ChatGPT). That requires buying roughly 3 million specialized computer chips. Two years ago, Oracle spent $6.9 billion a year on this kind of construction. This year it's $50 billion. The 30,000 people who got that email are funding the gap. Investment bank TD Cowen estimates the layoffs will free up $8 to $10 billion in cash flow, money going straight into chips and construction. Oracle filed a $2.1 billion restructuring plan with regulators in March, and nearly $1 billion had already been spent before the emails went out. Lenders are getting nervous. The cost to insure Oracle's debt against default has spiked to levels last seen during the 2009 financial crisis. Barclays downgraded Oracle's debt in November, warning the company is one step from "junk" status, the point where lenders consider you a serious default risk. Some banks have stopped lending to Oracle for these projects altogether. The gamble gets worse. CNBC reported on March 9 that OpenAI, Oracle's biggest customer for all of this, is already looking at newer, faster chips from Nvidia. Oracle ordered the current generation and spent billions building out a massive Texas facility. OpenAI may not fully expand into it. The chips improve faster than the buildings go up. Larry Ellison, Oracle's founder, owns 41% of the company. In September 2025, Oracle's stock hit $346, and Ellison briefly became the richest person alive at $393 billion. Today, the stock sits around $146. His fortune has dropped to roughly $201 billion in six months. Oracle is spending borrowed money to build data centers that could be outdated before they're finished, for a customer already shopping for newer equipment. 30,000 people woke up to a 6 AM email because that's what it costs to fund a $156 billion bet when your lenders are running out of patience.

Help me finish this list. What is your number 3?

@asmartbear This is the order most first-time founders get wrong. They start with a product idea and then try to find a market. The ones who win start with a problem they personally understand deeply. Founder market fit is not optional. It is the prerequisite for everything else working.

Without founder/market fit, this team won't be able to execute. Without product/market fit, this product won’t be purchased. So it’s not “which one” or “it’s a balance.” It’s: Both.

@agazdecki @acquiredotcom Agencies that specialize in one platform and one outcome are the easiest businesses to sell. Clear revenue model, recurring clients, and a transferable playbook. The generic full service agencies sit on marketplaces for months.

Another profitable agency crushing it! Live on @acquiredotcom: Shopify growth agency helping premium DTC brands turn existing traffic into revenue through UX, strategy, and development. > $475K ARR > $835K TTM revenue > $354K TTM profit Full listing: app.acquire.com/startup/aKnLPL…

@nathanbarry First job was building WordPress sites for local businesses at 19. Learned that clients do not actually know what they want until you show them something. That lesson carried into SaaS. Ship fast, iterate on real feedback, not spec docs.

What was your first job? What did you learn from it?

@robwalling @startupspod 825 episodes is insane consistency. Most podcasts die before episode 20. The compounding effect of showing up for 16 years is what most people underestimate about content. This pod has probably generated more SaaS founders than any accelerator.

16 years ago today, the first episode of @startupspod went live. It’s now old enough to drive. 825+ episodes later, still shipping. Appreciate everyone who’s listened, reviewed, shared, or sent in a question along the way.

@staysaasy The worst version of this is when they say it publicly in front of the remaining team. Everyone takes mental notes. If leadership trashes people who leave, they will trash you too when you go. Best managers I have worked with say nothing but good things about departing teammates.

One of the easiest ways to spot a bad manager is when the say “they weren’t that good anyway” after someone quits.

One customer went from $4,500/month to $1,500/month overnight. Same team size. Same document volume.

We have seen teams lose $5,000+ to missed cancellation windows.