GitHub
GitLab
BitBucket
VS Code
Git
Treehouse
Pantheon
CodePen
Topolog
monday.com
Asana
ClickUp
Trello
MS Project
PlanningPME
Planoramic.io
Topolog turns any goal into a dependency graph and schedules your days around it. You get a structured plan, a completion spectrum, and a task list that adapts as you mark them done. Every plan is a real program, so the dates and odds are computed, not guessed.
GitHub
TopologTopolog's answer:
Built by a solo founder with 14 years across Meta, Media.net, Amazon and others. After watching countless projects miss deadlines, not from incompetence but from tools that gave one fake date, I set out to build a planning engine that takes uncertainty seriously. The result is Topolog: a formally total scheduling language, a deterministic Monte Carlo engine, and a Bayesian self-tuning scheduler. Built entirely solo with Claude Code and Devin as AI engineering partners. Zero VC, zero team, 100% ownership.
Topolog's answer:
Anyone running a goal with real dependencies and real stakes: technical project managers, engineering managers, founders, and ambitious individuals planning complex personal projects like home renovations, album productions, or marathon training. The unifying characteristic is feeling the pain of planning tools that lie about deadlines. Topolog is for people who want to know their actual odds, not a false sense of certainty.
Topolog's answer:
Every other planning tool gives you one deadline, the one you'll miss. Topolog gives you the full picture: a dependency graph that knows what blocks what, a Monte Carlo completion spectrum showing your real odds, a critical path that updates as you execute, and a budget tracker tied directly to your probability of success. MS Project has critical path but no probabilistic engine. Monday and Asana have boards but no complete dependency model. AI tools hallucinate dates. Topolog computes them.
Topolog's answer:
Topolog treats every plan as a program. Plans are written in TOL (Total Orchestration Language), a formally total, decidable language where the scheduler and Monte Carlo engine compute dates and probabilities deterministically. The AI drafts structure but never touches the maths. You get a completion spectrum (a probability distribution over outcomes), honest deadline ranges (a floor and a ceiling, never one date you'll miss), and a Bayesian self-tuning scheduler that learns your real pace from timestamps alone. The planning language is public, you can author plans with any AI and run them through Topolog's engine.
Topolog's answer:
Topolog is a TypeScript-first web app built around a custom stochastic-planning engine:
Frontend: Next.js 15 (App Router) with React 18 and TypeScript, styled with Tailwind CSS. The interactive plan canvas uses dagre / ELK (elkjs) for graph layout.
Core engine: an in-house DSL ("TOL") plus a Monte Carlo stochastic-forecasting engine, written in pure isomorphic TypeScript so it runs identically on the server and in the browser.
Backend & data: Supabase (PostgreSQL, auth, and SSR), with the API layer on Next.js route handlers. Stripe handles billing.
AI authoring: a model-router layer that calls GPT (OpenAI), and Mistral for plan authoring and review.
Infra & quality: deployed on Vercel (Analytics + Speed Insights), error monitoring via Sentry, and tested with Jest + Playwright.
Based on our record, GitHub seems to be more popular. It has been mentiond 2463 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The core of the ecosystem is the official open-source server hosted on GitHub. It is written in TypeScript and implements the full MCP specification. - Source: dev.to / about 5 hours ago
This is why the gate needs a trace it can trust, and why AgentLens is the other half of this workflow. agent-eval scores and gates the output; AgentLens captures the trace of how the agent got there โ every model call and tool step, the resolved inputs (not the templated ones), the raw outputs. That trace is exactly the unforgeable, agent-didn't-author substrate that Tier 1+2 need to score against. Without it,... - Source: dev.to / about 17 hours ago
## Tell Git to start tracking your project Git init ## Take a snapshot of all your current files Git add . ## Save this snapshot with a description Git commit -m "Initial commit from AI tool" ## Connect your local project to GitHub ## Get repository URL from your GitHub page ## it looks like https://github.com/your-name/your-repo.git Git remote add origin PASTE_YOUR_URL_HERE ## Upload your code to GitHub Git... - Source: dev.to / 10 days ago
Conclusion Next time Git insists a private repository doesn't exist, skip editing your config file and head straight to the Windows Credential Manager. Wiping out the stale git:https://github.com entry forces a clean handshake, getting you back to coding in less than a minute. - Source: dev.to / 11 days ago
Gitea is where all private repositories live: infra configs, personal projects, anything I don't want on a third-party server. Public projects still go to GitHub because that's where the audience is, but a number of those GitHub repositories are mirrored back to Gitea as a local backup. The split is simple: Gitea for control and resilience, GitHub for reach. - Source: dev.to / 12 days ago
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ClickUp - ClickUp's #1 rated productivity software is making more productive projects with a beautifully designed and intuitive platform.