Tim

Founder & CEO @Bookipi1. 10 years in construction → tech. Building AI-first software for SMBs. Sharing what I learn along the way.

[Tim @gdaytim]

The 'failurepreneur' realisation: every failed startup sharpened something. The problem wasn't the failures. It was not learning fast enough from each one.

[Tim @gdaytim]

Embrace mistakes, yes. Avoid over-planning, also yes. Most founders plan to feel in control. The plan is rarely what saves you.

[Tim @gdaytim]

GPT-5.6 Sol is your new unfair advantage. Stop pitching abstract ideas. Use its deep reasoning to ship functional SaaS MVPs and high-fidelity frontends for clients in 48 hours.

[OpenAI @OpenAI]

Introducing ChatGPT Work, a new agent in ChatGPT powered by Codex and GPT-5.6.

It can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.

It’s a whole new way to get work done.

[Tim @gdaytim]

Seek early feedback relentlessly. Not to confirm the idea. To kill the bad parts before you've built too much around them.

[Tim @gdaytim]

The thing I got most wrong early: energy management. I confused 14-hour days with work. They overlapped. But they weren't the same thing.

[Tim @gdaytim]

With GPT-5.6 Sol dropping, maybe a reset for the tokens we rushed spending before the 7th? @claudeai

[Claude @claudeai]

We're extending access to Claude Fable 5 on all paid plans through July 12.

[Tim @gdaytim]

When you run a company, you learn quickly that the most powerful tool is not always the right tool for every job.

Fable 5 is very capable. But if you use it for an entire Claude Code session, it will happily spend frontier-model money on work that does not need frontier-model judgement.

That is not an AI problem. It is an operating problem.

The better setup is to treat Fable 5 like an orchestrator.

Let it plan, break down the task and decide where the real judgement is needed.

Then route the work properly.

Opus for architecture, debugging and algorithm design.

Sonnet for routine implementation, tests and formatting.

Same workflow. Better allocation. Lower cost.

This is the part many teams miss with AI. The leverage does not come from always using the strongest model.

It comes from designing the system so the right model does the right work.

[Jeremy Jarry @JarryJeremy]

Thank you to @EPodcastNetwork for having me on to share @Bookipi1 ’s journey to becoming an AI-native organisation with @gdaytim

AI-native isn’t about adding more tools. It’s about changing how teams think, ship, decide and create value for customers.
#ainative

[Tim @gdaytim]

Started Bookipi in a cafe. 60,000 businesses in year 1. 150 new sign-ups a day at peak. Declined a buyout offer. Still not sure if that was smart or stubborn. Maybe both.

[Tim @gdaytim]

I was a tiler. Then I taught myself to code. Not because I had a plan. Because the problem was so obvious and nobody was solving it simply enough.

[Tim @gdaytim]

7 failed startups before Bookipi. Each one felt like the one. Each one wasn't. The 8th wasn't a better idea- it was the same stubbornness, finally aimed at the right problem.

[Tim @gdaytim]

We cancelled Figma.
Every designer across our product teams now designs with AI. No fallback. We burnt the bridge.
Designers design in code. Collaborate through Git.
The handoff problem is solved when there's nothing to hand off.

[Tim @gdaytim]

Bots don't navigate menus. They need APIs, CLIs, and structured output. If an agent can't drive your product, your market is already shrinking.

[Tim @gdaytim]

Since 2024 every startup has bolted on an LLM to generate content. By 2026 nobody buys a separate product to generate content. They pay Claude for that.

[Tim @gdaytim]

The per-product agent is losing to the cross-product platform. If your agent only knows your app, it already lost.

[Tim @gdaytim]

Branding your own AI agent was a 2024/25 move for SaaS companies. Customers don't want your agent. They want their agent to reach into your data.

[Tim @gdaytim]

Every SaaS company shipped its own branded AI agent. Salesforce's Einstein, HubSpot's Breeze, Atlassian's Rovo, and on and on. Users didn't want ten agents. They wanted one that works across every tool they own