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Self Improving Sales Agents
Self improving Sales agent swarm
Closed-loop outbound for any market: research → score → draft → CHP lock → learn. CrewAI draft brain; deterministic score/learner; no auto-send. - icohangar-ops/self-improving-outreach
I built this because outbound systems often optimize for producing more messages, not for learning which signals, ICP features, and message angles actually lead to meaningful conversations.
The goal was a closed-loop workflow: research a lead, score it against explicit ICP weights, draft and critique the message, require a human approval lock, and then learn from real outcomes. I also wanted to keep the system trustworthy: deterministic scoring and learning remain outside the LLM, and the repo never auto-sends outreach.
The approach evolved from a simple AI drafting experiment into a more structured pipeline with failover, evidence packs, audit logging, human approval, and a learner that updates both ICP weights and message patterns over time. CrewAI now serves as the drafting brain inside the workflow, rather than being responsible for the decisions that govern readiness or learning.
About Self Improving Sales Agents on Product Hunt
“Self improving Sales agent swarm”
Self Improving Sales Agents was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #87 on the daily leaderboard. Closed-loop outbound for any market: research → score → draft → CHP lock → learn. CrewAI draft brain; deterministic score/learner; no auto-send. - icohangar-ops/self-improving-outreach
On the analytics side, Self Improving Sales Agents competes within Sales, GitHub and Growth Hacks — topics that collectively have 67.9k followers on Product Hunt. The dashboard above tracks how Self Improving Sales Agents performed against the three products that launched closest to it on the same day.
Who hunted Self Improving Sales Agents?
Self Improving Sales Agents was hunted by Sam Desigan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Self Improving Sales Agents including community comment highlights and product details, visit the product overview.
Sam Desigan