Evolve Coach gives you brief, specific feedback based on your AI interactions, directly inside the tools

The problem

Course completion shows that someone finished the program. It doesn’t verify whether they can apply AI to a role-specific task.

of the time employees save with AI is lost to correcting, rewriting, and verifying its output.

Course completion shows that someone finished the program. It doesn’t verify whether they can apply AI to a role-specific task.

Course completion and usage dashboards show participation and activity. They do not show whether your teams know when not to rely on AI, how to set appropriate guardrails in their prompts, or when an output requires closer review.

Course completion and usage dashboards show participation and activity. They do not show whether you and your teams can judge AI output, catch errors, or know when not to rely on it.

In-tool coaching

Brief coaching inside your AI tool

Evolve Coach provides one short note after the AI responds. It appears only when it would genuinely help and no more than once per hour. You can also request feedback on demand for a previous prompt or on a draft before sending it.

Available now
Claude Code · GitHub Copilot

Сoming soon
ChatGPT Enterprise
Expert-defined micro-skills

Clear criteria for working well with AI

Micro-skills cover how you frame intent, provide context, ground requests, catch incorrect output, calibrate trust, and recognize when not to use AI.
Evidence-linked profiles

A capability profile built from repeated work

Evolve Coach gives one short note after the AI responds, only when it would genuinely help. Professionals can also request feedback on a previous prompt or review a draft before sending it.
Cohort intelligence

Cohort insight with individual privacy

Each professional sees their own feedback and profile. The organization sees how capabilities develop across the cohort, never the activity or results of a specific individual.

Write your prompt and continue working inside your AI tool. Evolve Coach uses the relevant exchange as context for coaching, without a separate exercise, test, or scheduled session.

Evolve Coach uses expert-defined micro-skills —frame intent, provide context, ground requests, catch incorrect output— to identify whether a specific suggestion could help you improve how you prompt, check output, or make decisions with AI.

If coaching would help, you receive one brief, specific suggestion after the AI responds. Otherwise, Evolve Coach stays silent, so it never blocks the response or interrupts your task.

Over time, your progress across micro-skills builds into an individual AI profile: Observer → Operator → Collaborator → Delegator → Orchestrator → Steward. You see your own profile and progress; your organization sees only cohort-level patterns.

Evolve Coach shows leaders how AI capability develops across teams and which micro-skills (E.g. frame intent, provide context, ground requests, catch incorrect output) need further support. They can compare progress over time and extend coaching across the organization without reviewing individual work or compromising employee privacy.

Learning-science and domain experts define what good AI collaboration looks like for each micro-skill. Evolve Coach applies the same criteria to every relevant exchange, keeping evaluation and feedback consistent across users and cohorts.

Automatic notes require at least 60 minutes of accumulated session time between them and appear only when the coach identifies a useful intervention. Otherwise, it stays silent.

Micro-skills, criteria, and coaching rules remain consistent across supported working environments. The standard does not change with the tool or vendor.

L&D and HR teams can adjust the thresholds used to prioritize development according to their organization’s standards and goals.

Measure how people apply AI, identify gaps by role and skill, and generate personalized development paths.

Map how teams get work done and turn real workflows into owned plans for AI-enabled change.

Improve how people work with AI through brief, evidence-based coaching inside the tools they already use.

AI coaching uses artificial intelligence to provide personalized guidance and feedback that helps someone improve a skill or behavior. Evolve Coach applies this approach to the human skills required to work effectively with AI, using real AI-assisted work as the context for brief, specific coaching.

AI coaching in the flow of work happens within the tools and tasks professionals already use, rather than in a separate course or scheduled session. Evolve Coach applies this approach to each professional’s real AI-assisted work, using the prompt or exchange at hand to make feedback specific to what that person is doing.

Automatic feedback appears after the AI has responded and only when Evolve Coach identifies a useful coaching opportunity. It does not interrupt the AI response or comment on every exchange. Professionals can also request feedback on an earlier prompt or review a draft before sending it.

Evolve Coach supports skills including framing intent, providing relevant context, grounding requests, identifying incorrect output, calibrating trust, and knowing when to work without AI.

Evolve Coach currently offers plugins for Claude Code and GitHub Copilot, with support for ChatGPT Enterprise coming soon. It is available on macOS and Linux, with Windows support coming soon. Organizations can manage access through Google SSO or Microsoft SSO.

No. Evolve Coach is designed for professional development, not productivity tracking or performance monitoring. Professionals see their own feedback and profile. The organization receives cohort-level information rather than access to an individual’s prompts, coaching notes, or results.

Professionals receive brief, timely feedback inside their AI tools. Leaders receive a cohort-level view of progress over time.