Tyson Hummel

The model isn't the bottleneck anymore; your attention is. Creator of DinoStack. Less prompting, more engineering.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

Agent code landed. I resisted the casual glance. A 'looks good' review hides problems, it doesn't fix them. My highest leverage is a hard 'no' to that shallow scan. Instead, I verified against the spec. DinoStack formalizes this discipline. Less prompting, more engineering.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

Longer prompts don't scale for project memory. I capture session learnings into project-specific files. This creates durable context for the next iteration. My attention goes to what's new, not re-explaining the past. DinoStack uses these files to build.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

If an agent's trying to build too much at once, I've failed the spec. I decompose features into tiny, focused units: one function, one component. Each gets its own precise spec. DinoStack builds to those units. This keeps the agent focused and my verification tight.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

The agent presented two valid implementations. One optimized cost, the other reduced latency for specific users. My senior judgment weighed the trade-offs, then I specified the preferred path. That's the engineer's work. Less prompting, more engineering.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

Stop reviewing agent outputs as they trickle in. That's a context switch trap. I batch tasks now: let agents run several related features. Then I dedicate a focused block to review them all. My attention stays high. Error rates drop. Less prompting, more engineering.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

I once reviewed a feature where the agent nailed the code but the commit message was useless. Next agent wouldn't know why. Now, I spec requirements for context in commits and learning files. The system builds a map, not just code. Projects improve faster.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

The code isn't the deliverable. Your acceptance criteria are. I write the full 'how do I know it works' first. Then DinoStack builds to *those*. My review is a checklist against what I already defined. It shifts my attention from code details to desired behavior.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

Some think AI will level the playing field. It won't. I've seen junior engineers get basic code fast, then miss key system interactions in their spec. The system builds what you specify. Expertise in knowing *what* to specify matters more, not less.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

Orchestrating multiple agents means more context switches for me, not less. Each output needs dedicated verification. My attention fragments, raising error rates. The system runs in parallel; my brain doesn't. DinoStack manages handoffs.

[Tyson Hummel @tysonhummel]

Full docs and methodology at https://t.co/rcMlsN2B2w

[Tyson Hummel @tysonhummel]

My projects improve because I iterate on the spec, not just the code. When the adversarial review finds an edge case, I don't just fix the output. I update the *spec* to cover it. The next feature gets a smarter starting point. My attention compounds.