Devin Review 2026

Windsurf (now Devin Desktop)

The agentic IDE formerly known as Codeium, now under Cognition

Few tools in this list have had a stranger year than Windsurf. It started as Codeium, a lightweight free autocomplete extension that developers recommended to students and budget-conscious teams who didn't want to pay $20/month for Copilot. It rebranded to Windsurf in late 2024 as it grew into a full agentic code editor built around a feature called Cascade. Then came 2025: OpenAI attempted a $3 billion acquisition that collapsed over Microsoft's contractual rights, Google hired away the founding team and roughly 40 senior engineers in a reverse-acquihire, and Cognition — the company behind the autonomous coding agent Devin — acquired the remaining IP, brand and 210 employees for around $250 million in December 2025. Then, on June 2, 2026, Cognition folded the product under its own brand entirely, renaming it Devin Desktop. What you actually get today is a VS Code-fork editor with Cognition's proprietary SWE-1.6 model (successor to SWE-1.5) powering code generation, plus a genuinely distinctive feature: a handoff workflow to Devin's cloud agent for longer autonomous tasks, letting you start work locally and continue it in the cloud without switching tools. Cascade, Windsurf's original agentic engine, was end-of-lifed on July 1, 2026 in favor of "Devin Local" as the default local agent — if you see Cascade referenced anywhere, that's now outdated. Pricing held steady through the ownership changes: Free (unlimited Tab autocomplete plus a light shared quota), Pro at $20/month (standard quota, access to Claude, GPT-5-series and Cognition's own models), Max at $200/month (heavy quotas for all-day use), and Teams/Enterprise tiers with SOC 2, HIPAA, FedRAMP/DOD and ITAR compliance. If you're evaluating it, go in aware that the product's direction now depends entirely on Cognition's roadmap for Devin — worth weighing against Cursor's relative stability if long-term continuity matters to your team.

Tabnine

Privacy-first AI code completion with zero code retention

Tabnine predates GitHub Copilot — it launched in 2018 as one of the first AI code completion tools — and has built its entire identity around privacy and deployment control rather than trying to out-feature Cursor or Windsurf on agentic capability. Its core promise is zero code retention (your code is never stored or used to train shared models) plus genuinely flexible deployment: fully SaaS, VPC, on-premises, or completely air-gapped for organizations that can't send code outside their own network under any circumstances. A meaningful change worth knowing: Tabnine retired its free tier entirely in 2024. Where it once offered a generous free plan that made it a common recommendation for students and budget-conscious developers, it's now a paid-from-day-one product. The Code Assistant plan runs $39/user/month (annual billing) for completions, IDE-integrated chat, IP protection and flexible deployment; the newer Agentic Platform tier adds autonomous multi-step agents, MCP tool support and a CLI for $59/user/month. At those prices, Tabnine sits well above Cursor Pro ($20/month) and GitHub Copilot Pro ($10/month) for comparable core completion quality — the premium is specifically for the privacy guarantees and deployment flexibility, not raw AI capability. It's the right choice for security-conscious enterprises, defense contractors, and regulated industries that genuinely need air-gapped deployment or contractual zero-retention guarantees; for a solo developer or small team without those specific requirements, a cheaper competitor will likely deliver similar day-to-day value.

Zed

Trending

The fastest AI-native code editor, built in Rust by Atom's creators

Zed is built by the team behind Atom (the editor Microsoft acquired and later sunset) and Tree-sitter, and its entire premise is that a code editor should feel instant — GPU-accelerated rendering, multi-threaded indexing and a from-scratch Rust foundation instead of the Electron/JavaScript stack most competitors, including Cursor and Windsurf, are built on. The performance difference is measurable and real: benchmarks show roughly a 0.6-second cold start versus 4.5 seconds for Electron-based editors, and single-digit-millisecond input latency versus roughly 30ms elsewhere — genuinely noticeable if you work in a large repository daily. AI is native to the editor rather than bolted on: an Agent Panel handles chat, inline edits and multi-file changes, paired with Zeta2, an open-weight edit-prediction model for low-latency next-edit suggestions similar to Cursor's Tab feature. Zed connects to Claude, GPT-5.4, Gemini and local Ollama models, and — distinctively — supports the open Agent Client Protocol (ACP), letting you drive the editor with external CLI agents like Claude Code or Codex without needing a separate Zed AI subscription at all. Real-time multiplayer collaboration, with live cursors and shared editing sessions, is built into the core rather than requiring a plugin. Pricing is refreshingly simple: the editor itself is fully open source (GPL/Apache) and free forever, with every core feature unlocked regardless of payment. AI comes in three tiers — Personal ($0 forever, 2,000 accepted edit predictions/month, unlimited AI with your own API key), Pro ($10/month, unlimited predictions plus $5 of included hosted-model tokens), and Business ($30/seat/month, org-wide policies and centralized billing). At half of Cursor's price for comparable AI capability, plus a smaller but growing extension ecosystem, Zed is the strongest pick for developers who prioritize raw speed and openness over the largest plugin marketplace.

Lindy

Prebuilt 'AI employees' for everyday business operations

Lindy's pitch is the fastest path from zero to a working AI agent handling real business operations: prebuilt "AI employees" for common tasks — email triage, meeting scheduling, CRM updates, customer support — that you can stand up in minutes via a drag-and-drop builder, rather than assembling an agent from scratch. It includes 4,000+ integrations and voice-agent capabilities alongside its core workflow automation, positioning it as more turnkey than Relevance AI's build-your-own-workforce approach. Its credit-based pricing meters every action, with cost scaling by complexity: a simple step costs roughly 1 credit, while email parsing or multi-step workflows burn 5-10 or more credits per run — worth understanding before assuming a flat monthly rate covers unlimited usage. Independent comparisons consistently place Lindy as offering better value than Zapier per dollar of task automation, largely because its pricing tiers include a meaningfully larger effective task allowance per plan level. With a free tier (limited agents and tasks) and paid plans starting around $50/month, Lindy sits above Relevance AI's $19/month entry point but below CrewAI's technical, developer-oriented positioning. It's the strongest fit specifically for non-technical teams wanting fast, ready-made automation of everyday operational tasks — email, scheduling, CRM hygiene — without the setup overhead of a code-first framework or the build-your-own-agent-team complexity of Relevance AI.

AgentGPT

Browser-based autonomous agents — free hosted demo or self-hosted

AgentGPT was among the earliest browser-accessible autonomous agent tools, letting you set a goal in plain language and watch an AI agent break it down into sub-tasks and attempt to complete them with minimal ongoing supervision — no local installation required for the hosted demo version. It's built on the same autonomous-agent philosophy as tools like AutoGPT, but with a more accessible, browser-first entry point that made it a popular way for non-developers to first experience agentic AI. Its pricing structure is genuinely two-tiered in a way worth understanding clearly: the hosted demo offers limited free usage with no setup, while a separate self-hosted, open-source version follows a bring-your-own-infrastructure cost model — you pay only for VPS hosting (roughly $5-20/month) plus your own LLM API key usage, with no platform subscription fee at all for the self-hosted path. Managed/paid tiers on the hosted platform run around $40/month for higher usage limits and premium features. The honest limitation shared across early autonomous-agent tools like AgentGPT: they tend to consume more API tokens than more targeted platforms, since the autonomous, exploratory approach generates more LLM calls per completed task than a narrowly-scoped agent would. It remains a reasonable low-commitment way to experiment with autonomous agent behavior — set a goal, watch it work — before committing to a more structured, business-operations-focused platform like Lindy or a developer framework like CrewAI for production use.

CrewAI

Open-source multi-agent orchestration, free framework plus a managed cloud

CrewAI is both a free, MIT-licensed open-source Python framework for orchestrating multiple collaborating AI agents and a managed hosted platform (CrewAI AMP) for teams that don't want to run it themselves — a dual identity that's core to understanding its actual cost. The open-source framework, with over 50,000 GitHub stars and a reported 2 billion agent executions in the trailing 12 months as of 2026, lets developers build "crews" of specialized agents (a researcher, a writer, a reviewer) that divide and coordinate complex multi-step tasks, and it's used by a majority of Fortune 500 companies according to the company's own disclosures. CrewAI's public cloud pricing has genuinely changed multiple times and is worth getting straight: a $25/month Professional tier (100 executions/month) existed from its October 2025 AMP launch through spring 2026, then was removed entirely. As of mid-2026, the public cloud pricing is two tiers only — Basic, free with 50 workflow executions/month and full core platform access (not a crippled trial), and custom-quoted Enterprise for organizations needing compliance certifications and dedicated support (estimated $60,000-$120,000 annually in third-party analysis). If you're reading an older article citing a $99/month or $25/month self-serve mid-tier, that pricing has been discontinued. The cost that catches most teams off guard isn't the platform fee at all — it's LLM API usage. Because CrewAI counts one "execution" as a full crew run regardless of how many agents are involved or how many tokens they consume internally, a crew with 10 agents making extensive LLM calls costs the same one execution as a single-agent crew, but the underlying API bill can be dramatically higher. Production costs for token-hungry multi-agent workflows commonly run $1.50-12/hour depending on task complexity — budget for that separately from whatever CrewAI's own platform tier costs.

Manus

Trending

General AI agent that completes real tasks end to end

Manus is a general-purpose autonomous AI agent that goes beyond chat: give it an objective and it plans, browses the web, writes and runs code, manipulates files and delivers a finished artifact — a research report, a spreadsheet, a slide deck or a deployed web page. Each task runs inside its own cloud sandbox with a live view of what the agent is doing, so you can watch the browser tabs, terminal commands and files it creates in real time and step in when needed. Tasks continue running even after you close the tab, and Manus notifies you when the deliverable is ready. The platform is credit-based: simple tasks cost a few credits, long autonomous research runs cost more. Teams use Manus for competitive research, lead list building, data cleanup, market analysis and prototype generation — work that used to take an analyst a full day.

Relevance AI

Build a coordinated 'AI workforce' of role-based agents

Relevance AI's core concept is an "AI workforce": rather than one general-purpose assistant handling every request, you build narrowly-scoped agents with distinct roles — a research agent, an SDR agent, an ops agent — that work together as a coordinated team, each using only the tools and information assigned to its specific job. That multi-agent orchestration approach makes it particularly strong for go-to-market teams building sales and revenue-operations workflows where several specialized tasks need to hand off to each other. A significant pricing restructure took effect in September 2025 and remains the current model: costs split into Actions (what an agent actually does — API calls, tool use) and Vendor Credits (the underlying LLM model costs), with no markup on Vendor Credits and the option on paid plans to bring your own API keys to bypass them entirely. The free tier includes 200 Actions/month plus $2 in bonus vendor credits — useful for initial testing, but genuinely difficult to forecast real monthly spend from, since usage compounds quickly once agents run continuously or handle complex, multi-step tasks. Paid plans run from roughly $19/month for individuals up to about $199/month for teams, positioning it as more affordable at the entry level than Lindy (~$50/month) but with real usage-based cost uncertainty that Lindy's flatter-feeling tiers avoid. It's best suited to teams that want a genuine multi-agent "workforce" model for sales or ops specifically, and are comfortable actively monitoring Actions and Vendor Credit consumption rather than a fully predictable flat bill.

Genspark

All-in-one AI agent for search, docs, sheets and calls

Genspark is an agentic AI workspace built around Super Agent — a planner that picks the right model and tool for each step of a job. Ask it a question and it produces a Sparkpage: a generated, cited research page rather than a list of blue links. Beyond search, Genspark bundles AI Slides, AI Sheets, AI Docs, an AI Browser and an AI phone-call agent that can ring restaurants or vendors on your behalf. That combination makes it one of the broadest consumer agent platforms currently shipping, and a practical alternative to stitching together five separate subscriptions. Credits are shared across every tool, so a single plan covers research, document creation and automation. Genspark is popular with solo founders, consultants and small marketing teams that need a generalist assistant rather than a specialised one.

Manus

Trending

General AI agent that completes real tasks end to end

Manus is a general-purpose autonomous AI agent that goes beyond chat: give it an objective and it plans, browses the web, writes and runs code, manipulates files and delivers a finished artifact — a research report, a spreadsheet, a slide deck or a deployed web page. Each task runs inside its own cloud sandbox with a live view of what the agent is doing, so you can watch the browser tabs, terminal commands and files it creates in real time and step in when needed. Tasks continue running even after you close the tab, and Manus notifies you when the deliverable is ready. The platform is credit-based: simple tasks cost a few credits, long autonomous research runs cost more. Teams use Manus for competitive research, lead list building, data cleanup, market analysis and prototype generation — work that used to take an analyst a full day.