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EstimateGPT – Software planning and estimation tool

Hacker News

EstimateGPT – Software planning and estimation tool

One hard problem customers face with software outsourcing is that estimating the project cost takes days and sometimes weeks. Engaging with software dev agencies and running RFPs is even more lengthy and requires commitment and resources. Playing with GPTs, I found some satisfactory results it can get, given the proprietary data I provided it with. Introducing EstimateGPT: A software development planning assistant and custom GPT tool to quickly get a draft estimate and plan the project. It uses the redacted data of estimates we had done by hand for the last 5 years, and it was given a context and instructions that apply to software outsourcing projects. Here are some examples: 1) https://chat.openai.com/share/d2a8aa16-26aa-4971-a20d-d62d450670ea 2) https://chat.openai.com/share/b4b36eba-c225-4287-b631-4f73003831ce It certainly does not make ideal estimates and may miss something or hallucinate, but the results seem to be close enough to what you may generally find across the industry. Would be great if you could try it out and share some of your thoughts. It works great with PRD/SRS, and you might need to get one handy to speed up the process. Feel free to copy a sample from the example. Here is the EstimateGPT link (requires ChatGPT Plus subscription): https://chat.openai.com/g/g-Cghb6X2U7-estimategpt

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
AppSumoStrong fit for a featured deal · Strong signals: plus · Missing: platform, intuitive, reviews
51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: context, chatgpt, openai · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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