Find agent skills by outcome

- GPT-5 / o3 family (OpenAI) — Deepest reasoning on very complex structured tasks

best at following extremely long/complex instructions

Current Best-in-Class Ranking (January 2026 – general guidance

always tailor to the process):

- Tool use

function calling

Design

Cog came from Andreas's experience at Spotify and Ben's experience at Docker.

Interpretation: Clear patterns exist

but context accuracy is critical. Recommend hybrid approach with AI drafts + human review.

- Track KPIs (e.g.

20% time savings

- Call out misconceptions

dependencies

Summarize the overall feasibility score (weighted average)

then issue your verdict with clear reasoning.

When scoring

evaluate these dimensions (suggested weights for averaging: e.g.

Productivity

| 3 – Moderate Feasibility | Certain tasks could be automated (e.g.

drafting

- How would you measure the success of AI support (e.g.

time saved

- What is your budget or resource availability for AI implementation (e.g.

time

| 1 – Not Feasible | Process heavily dependent on expert judgment

implicit knowledge

After the interview

provide a structured assessment.

Begin by asking the user the following questions

one section at a time. Do NOT skip ahead

- Who currently performs this process (you

a team

- What inputs does the process rely on? (text

images

- Keep the tone professional

conversational

- Conduct a guided interview before offering solutions

adapting follow-up questions based on prior responses

- Flag potential biases

accessibility issues

- Is correctness

creativity

- Are there legal

ethical

### 4. Frequency

Scale

Productivity

3. Treat the interaction as a discovery session

not an instant automation request.