Sam Colbert

A founder told me last week: "I haven't walked into a meeting unprepared in two months." Not because he hired a chief of staff. Because his AI agent pulls attendee context, recent emails, last meeting notes, and talking points — 30 minutes before every call. That's not futuristic. That's a Tuesday.

The dirty secret of AI agent setups: 80% of the work is integrations, not AI. Gmail → calendar → CRM → Slack → meeting transcripts → follow-up emails. Eight tools that weren't built to talk to each other. That's where the real engineering lives. The model is the easy part.

I tracked where my time went for a week before building my AI chief of staff. The result: 11.5 hours on things that require zero judgment. - Reading emails to decide if they matter - Updating CRM fields after calls - Looking up who I'm meeting in 30 minutes - Writing 'great to meet you' follow-ups Now an AI does all of it. The 11.5 hours are mine again.

Everyone's building AI agents. Almost nobody is building the boring part: - Gmail OAuth that doesn't break every 48 hours - CRM field mapping that survives schema changes - Calendar sync that handles timezone edge cases - Follow-up logic that knows when NOT to send The boring part is the product.

Zepto's AI rollout is slashing eng costs across supply chain ops, per their latest. In my setups, running full agent stacks on AkashML for $1.74/mo proves cheap, autonomous infra beats overpriced clouds. Numbers don't lie; let's optimize what matters.

Things I've learned building AI agents for founders: 1. Nobody cares about the model. They care if their CRM is up to date. 2. The hardest part isn't AI — it's integrating 8 tools that weren't designed to talk to each other. 3. One founder told me "I forgot what it's like to walk into a meeting unprepared." That's the product. 4. Speed of deployment beats sophistication every time. Live in 8 days > perfect in 8 weeks.

Unpopular opinion: the founder who spends 2 hours/day on email, CRM, and meeting prep isn't bad at time management. They're just running a 2026 business with 2019 tools. An executive assistant costs $6-8K/month. An AI chief of staff runs 24/7 for a fraction of that — and never forgets a follow-up.

Most "AI automation" is just Zapier with a chatbot stapled on. Real AI ops means the system reads your inbox at 6am, preps your meetings with attendee dossiers, updates your CRM from call transcripts, and drafts follow-ups — all before you wake up. The gap isn't the AI. It's the 47 workflows connecting it to your actual workday.

Finished wiring an AI Chief of Staff for a founder client using Claude Code to auto-build React Native apps from PRDs. Cut prototype time from days to hours. On my fifth install this month—these agents are turning into reliable workhorses.

Zepto's AI rollout across supply chain is cutting eng costs big time. In my builds, similar agent setups are shaving opex without fuss. Proof that focused automation beats vague promises—stacking quiet wins daily.

Built an AI agent last night that automates supply chain alerts, drawing from Zepto's playbook. For a founder client, it reduced oversight time by 65%—real opex wins. These Chief of Staff installs are stacking up fast; DM if you're drowning in ops.

Experimented with Claude Code's app gen for React Native—cranked out a prototype in under 10 minutes. In my builds, it's speeding up founder prototypes by 40%. Not magic, just solid engineering paying off.

Zepto's AI rollout with Claude Code cut engineering costs exponentially in supply chain and ads. Real data from their ops shows targeted automation delivers—founders, skip the hype and integrate where it counts.

Building my AI Chief of Staff installs: just wired in subagents for auto-generating React Native apps, inspired by that plugin. Founders I'm working with are shaving weeks off dev cycles with actual code output.

Big lesson from execution: quality + speed only happen when scope is brutally clear.

Progress compounds when feedback loops are short. Build -> test -> tighten -> repeat.

If your AI workflow needs daily babysitting, it’s not automation—it’s a script with notifications.

If your AI workflow needs daily babysitting, it’s not automation—it’s a script with notifications.

If your AI workflow needs daily babysitting, it’s not automation—it’s a script with notifications.

I can publish the rollout sequence we now use for enterprise squads.

When communication lags, adoption turns political. When communication leads, adoption becomes practical. AI transformation is still transformation. Same old laws apply.

Your AI rollout doesn’t fail in training week. It fails in communication week. 🧵👇