Aakash GuptaWe Ranked Every AI Tool for Product Managers — So You Don’t Have To
CHAPTERS
Tier-ranking the 2025 AI stack for product managers (rules + guest context)
Aakash Gupta sets up a tier-ranking episode focused on AI tools that matter for product managers in 2025. He introduces guest Anshumanni Rudra (ex-VP Product Hotstar, now GPM at Google APAC Payments) and frames the goal: pick practical winners across categories, not just hype.
- •Tier-list format to rank many AI tools quickly
- •Focus on PM workflows: discovery, roadmapping, docs, meetings, prototyping, agents
- •Guest credibility and why he’s suited to evaluate tools
- •Early hint that Claude Code is a standout for PMs
AI agent builders: automation power vs. usability (n8n, Make, Lindy, Airtable, Relay)
They compare popular agent/automation builders, weighing flexibility against technical barriers. Lindy emerges as the best PM-friendly agent builder due to its promptable, AI-assisted approach, while more technical tools are graded lower for typical PM use.
- •n8n: powerful visual automation, but technical; graded around B/B+
- •Make.com: less powerful than n8n and still technical; graded C
- •Lindy: PM-friendly agent building with AI prompting; graded S and category winner
- •Airtable AI: strong PM templates + integrations; graded A
- •Relay: easy to use but less advanced/integrated; graded B
AI prototyping tools: speed, backend realism, and “everything looks the same” (Lovable, Bolt, Magic Patterns, v0, base44)
They assess AI prototyping tools for turning ideas into usable demos, debating front-end polish, backend capability, and reliability. Bolt, v0, and base44 lead the pack, while Lovable and Magic Patterns are seen as useful but limited for certain workflows.
- •Lovable: fast and pretty but outputs feel similar; backend weak; settles around B (initially discussed as A)
- •Bolt: stronger for complex, end-to-end apps and backend thinking; graded A
- •Magic Patterns: excellent for fast front-end prototyping; limited by no full vibe coding; graded B
- •v0: reliable, deployable with Vercel; backend support; graded A
- •base44: strong backend/app creation; graded A
Who wins prototyping? Bolt vs v0—and why reliability matters
Aakash and Anshumanni pick different winners among the top A-tier prototyping tools. The debate centers on structure and backend planning (Bolt) versus fewer errors and smoother iteration (v0).
- •Anshumanni prefers Bolt for structured planning and stronger end-to-end setup
- •Aakash prefers v0 due to stability and fewer debugging loops
- •Key evaluation criteria: error recovery, deployment ease, and backend realism
- •Takeaway: A-tier tools differ by workflow preference and tolerance for debugging
Replit Agent takes the crown for end-to-end building (and multi-agent workflow)
They elevate Replit as the best web-based environment for building full products quickly, especially for PMs who want a plan before code. Replit’s multi-agent capability and deployment strengths push it to the top tier for prototyping/vibe coding.
- •Replit prompts planning first (“what are we building?”) before writing code
- •Multi-agent mode: parallel work on bugs, frontend, documentation
- •Strong deployment and IDE heritage (pre-AI strengths carry over)
- •Replit graded S and positioned as prototyping winner in practice
Vibe coding IDEs & coding agents: Claude Code dominates (Windsurf, Claude Code, Cursor, Codex, GitHub Copilot)
The conversation shifts to coding agents and AI IDE workflows, where Claude Code becomes the clear standout. They compare usability, agent “taste,” and developer migration away from older incumbents like GitHub Copilot.
- •Windsurf: momentum concerns post-acquisition; graded C
- •Claude Code: highly agentic, huge context, terminal-native power; graded S and category winner
- •Cursor: strong VS Code fork, UI/UX details (agent on right) praised; graded A
- •ChatGPT Codex: agentic but less polished; graded C (borderline B/C)
- •GitHub Copilot: seen as lagging; graded D (still better than no AI access)
Big LLMs for PM work: diminishing returns and what’s actually useful
They evaluate general LLMs through a PM productivity lens, emphasizing that model improvements now feel marginal for many workflows. The discussion highlights deep research as useful but increasingly commoditized across providers.
- •Shift from model-number obsession to “fast vs thinking” modes is positive
- •Deep research is valuable, but differentiation is shrinking across tools
- •Product adoption challenge: ChatGPT at massive scale still hasn’t crossed the ‘next’ chasm for mainstream workflows
- •PM value judged by workflow impact, not benchmark wins
LLM rankings: ChatGPT, Perplexity, Claude, Grok, Gemini, Microsoft Copilot, Manus
They assign tiers to major LLM products and agentic research tools, with Claude leading for PM use. Manus stands out for running multiple parallel deep-research threads and scheduled tasks, while Grok and Microsoft Copilot are viewed as weak options for PMs.
- •ChatGPT: broadly used but ‘just okay’ for PM productivity; graded B
- •Perplexity: usage declined; graded C
- •Claude (Sonnet): default workhorse for writing + coding; artifacts feature; graded A (and declared best LLM)
- •Grok: limited usefulness/context; graded D
- •Gemini: strong deep research + top image/video models (NanoBanana, Veo 3); graded B
- •Microsoft Copilot: enterprise-limited version of ChatGPT; generally avoid if you have better options
- •Manus: parallel deep research + scheduled agent tasks; graded B+ (top of B tier)
AI experimentation & analytics: ‘vibe experimentation’ is coming (Amplitude, Kameleoon, Optimizely, Statsig)
They explore AI-assisted experimentation tools that can propose tests, create variants, and analyze outcomes. The category is promising but still maturing, with Kameleoon leading among the tools discussed.
- •Amplitude AI agents: suggest experiments and help implement; graded B (needs polish)
- •Kameleoon: prompt-based experimentation with higher quality; graded B and category winner
- •Optimizely: more marketing/homepage oriented; AI less developed; graded C
- •Statsig: strong experimentation analysis but not very AI-forward yet; graded C
- •Prediction: experimentation adoption by PMs could jump from ~5% to ~50% in 1–2 years
Discovery & customer intelligence: turning feedback into roadmap signals (Unwrap, Interpret, Dovetail)
They rank tools that aggregate and synthesize customer feedback across channels to recommend features and quantify impact. Interpret is positioned as the strongest, especially for B2B SaaS and revenue/ARR-oriented insights.
- •Unwrap: aggregates multi-channel feedback but earlier-stage; graded C
- •Interpret: B2B-focused, connects reviews (G2/Capterra), can estimate ARR impact; graded A and category winner
- •Dovetail: evolving from research repository to customer intelligence; powerful but less revenue/CRM depth; graded C
- •Observation: sentiment/feedback analysis remains surprisingly unsolved given years of ML history
AI browsers: ‘ask vs do’ and why most aren’t there yet (Comet, DIA)
They evaluate AI-first browsers as general-purpose agents that should execute tasks, not just answer questions. DIA is preferred for cross-tab chat and contextual writing/learning, while Comet is seen as underdeveloped for the promise of AI browsing.
- •AI browsers must handle ‘doing’ (actions) vs ‘asking’ (answers)
- •Comet: only delivers a few of the top expected features; graded D
- •DIA (Browser Company): chat with tabs + privacy-first posture; graded C and category winner
- •Key challenge: browsers need deeper user context to be truly useful assistants
Roadmapping platforms: modest AI so far (Jira Product Discovery, Pendo, Productboard)
They rate roadmapping tools on how well AI connects customer insights to prioritization and execution. Productboard stands out as the best-developed AI roadmap assistant among the options discussed.
- •Jira Product Discovery: helpful for dev-heavy teams, moderate AI; graded C
- •Pendo: interesting ‘AI usage analytics’ idea, but overall AI polish lacking; graded D
- •Productboard: stronger AI linking insights to roadmap items; graded B and category winner
- •Note: AI cost/usage governance is increasingly important for teams
Docs, meetings, dictation, video, and design: where PM leverage really is
They speed-rank productivity categories where PMs spend time: writing, meetings, dictation, and lightweight media/design. Granola and dictation tools stand out as high-leverage, while many marketing-oriented content tools are deprioritized for PMs.
- •Docs: Notion AI graded C (great desktop/web; mobile weak); Jasper/copy.ai/Grammarly/Gamma largely graded D for PM relevance
- •Meetings: Granola is S-tier for transcription + cross-meeting context + action-item recall; others (Otter etc.) land lower (generally C or worse)
- •Dictation: Super Whisper graded S; WhisperFlow graded A (strong habit-forming productivity gain)
- •Video: Loom seen as most relevant for PM async; others (Synthesia/Kling) graded D for PM needs
- •Design: Figma AI/Make graded B; UI Wizard graded C; Linear graded C; Zapier graded B as a workhorse
The #1 AI tool for PMs + building your personal AI tool roadmap
They crown Claude Code as the single best AI tool for product managers, then outline an approach for choosing tools based on where time is spent and which workflows need leverage. The episode ends with a practical recommendation to experiment intentionally and iterate based on impact.
- •Best overall AI tool for PMs: Claude Code
- •Suggested top stack after Claude Code: Super Whisper (dictation), Replit (build/ship), Lindy (agents)
- •How to build your AI roadmap: audit your week, identify time sinks, pick tools that map to those tasks
- •Experiment, measure productivity improvement, and keep only what compounds
