📰 Dev.to · Haley

A team I advised last year approved a new agent tool in eleven minutes. The demo was clean: the agent...

One trend I've noticed is that many vertical SaaS products don't struggle because of missing features...

Last month I watched a teammate approve an agent's database migration in about four seconds. The UI...

Every year, sports organizations invest in new engagement tools hoping to build stronger communities....

The decision that almost shipped Last month I watched a teammate paste an AI assistant's...

A reviewer on my team approved a pull request in four minutes last month. The diff was small: an AI...

"A study protocol for head-branch Copilot instructions that measures comprehension instead of acceptance alone."

A research-ready handoff card that retains task evidence, uncertainty, and reversibility when providers degrade.

A reviewable appointment-prep artifact and research protocol that separates source facts, user notes, open questions, and uncertainty.

A review-card and research protocol for binding human approval to exact actions and stop conditions.

Design and research an approval card that binds human consent to a versioned plan, evidence set, and consequence.

A product-design pattern for making specialized AI agent roles, evidence, authority, and handoffs visible to reviewers.

The K3 launch shows that AI products can succeed faster than their infrastructure. Here is an onboarding design that survives demand outstripping capacity.

Test whether human oversight creates understanding rather than collecting an approval click.

Pair every AI adoption metric with a counter-metric, consequence map, and challenge process.

Use GitHub’s repository-level Copilot metrics release to create an evidence-aware review card.

Design and research a review card for filtered selections, permission skips, and expiring undo.

Evaluate clarification and human oversight when two requirements cannot both be true.

Turn a new teen-AI safety discussion into an annotated design pattern with age-appropriate recovery, privacy, and research stop conditions.

A review-card and stop-condition framework for evaluating AI coding tasks before consequential action.

A study protocol for measuring evidence use, challenge behavior, escalation, and safe stopping in AI-assisted security review.

A review card should expose skipped tests, unread files, unavailable dependencies, and unresolved assumptions before presenting an approval action.

Google DeepMind's ATL Saathi pilot is a useful prompt to design educational AI around evidence, reflection, and teacher handoff.

A hosted AI dev platform is a design problem as much as an engineering one. Here is how to keep human oversight central when your team adopts MonkeyCode's SaaS.