Rohit Patil
Portfolio AI / ML Engineer Est. 2024

Rohit Patil

I teach machines to remember, reason, and act.

An AI/ML engineer building what makes AI agents actually capable — memory, orchestration, and the reasoning to carry long, complex work to the finish.

Currently intoagent memory
01 / Who

The short version of me.

Rohit Patil
Fig. 01Rohit Patil · Pune, IN

I build AI agents that can be trusted with real, long work.

Orchestration and harnesses for long-horizon tasks, complex multi-agent systems, retrieval that genuinely grounds them, and the memory and MCP tooling that sits underneath it all.

I care less about models that demo well than about systems that hold up — the same answer on the hundredth run as the first. That's the part I find genuinely fun.

Now Two-plus years shipping AI systems — currently at Indicus Software, Pune.
02 / Focus

The themes I keep returning to.

a. Operate The harness: planning, tool-use loops and long-horizon execution that recovers from failure.
b. Know Context engineering — the right information at the right moment. Where memory, retrieval and graphs live.
c. Act Tool & protocol design (MCP) — how an agent reaches out and changes the world.
d. Hold up Evaluation and reliability — the same answer on the hundredth run as the first.
e. Compound The system learns from itself — each run's outcomes distilled back into the context that drives the next.
f. Restraint Power isn't the point — appropriateness is. Lean cost and latency, real guardrails, a human kept in the loop.
A rough tally, so far
40+
MCP servers built
30+
AI agents built
80+
GenAI pipelines
25+
POCs delivered
03 / Work

A few things I've built.

№ 01

Fluently

2026 · live

The English tutor you can't catch teaching.

You add the words and phrases you want to use fluently, give the AI a persona, and just chat. Underneath, a hidden engine weaves your words in and scores how well you use them, and it keeps a living memory of your life, growing more familiar the more you talk.

  • Invisible pedagogy — its hidden mission is your vocabulary, but it never reveals the machinery. It just feels like a friend who picks good topics.
  • A judge that never interrupts — a second model silently scores every message and picks what you practice next by spaced repetition.
  • Memory it curates itself — living files on who you are and your life, edited by the agent mid-conversation.
  • Real product plumbing — Google sign-in, per-user isolation, and each user's own Gemini key encrypted at rest.
Visit fluently.fun →
Persona agentFull-stackLive
the arc of one word
Recognise it12
Use it, clumsy31
Use it, natural68
Yours now94
№ 02

Symposium

2026 · experiment

AI agents that think privately and speak socially.

A multi-agent framework built to make a discussion feel like a real room of people — not a tidy sequence of function calls.

  • A private inner life — each agent has hidden thoughts, memories, perceptions of the others, and its own motivations.
  • The floor is earned — before speaking, an agent decides whether it even wants to, then competes by urgency and social balance. No fixed turn-taking.
  • Public ≠ private — what an agent says can deliberately differ from what it's really thinking.
  • Mix and match — OpenAI, Anthropic and Google models, so different agents behave like different people.
View on GitHub →
Multi-agentSocial dynamicsMulti-model
a turn, internally
private › "I disagree — but is it worth the friction?"
urgency 0.62 · floor: contested
decision › speak, challenge gently
public › "I see it differently — what if memory, not turn order, drove this?"
№ 03

Smriti

2026 · open source

A second brain that remembers who you are — not what you saved.

A voice-first AI agent inspired by Andrej Karpathy's "LLM Wiki" pattern. It quietly compiles a living snapshot of your life, relationships and focus through ordinary conversation.

  • An identity.md working memory split into four layers — Core Identity, Life Phase, Events, Active Focus.
  • Time-based decay — entries are timestamped, and unreinforced memories sink deeper, the way we actually forget.
  • A synaptic knowledge graph — people and projects as markdown files with permanent 14-digit IDs, linked like Obsidian notes.
  • Talk or type — browser voice mode via Gemini Live, or local tools through MCP.
View on GitHub →
Voice-firstKnowledge graphMCP
identity.md · working memory
L1Core Identitypermanent
L2Life Phaseslow
L3Eventsdecaying
L4Active Focusvolatile
№ 04

Manthan

2026 · multi-agent

A council of AI experts, not a single chatbot.

For the hardest decisions, one viewpoint isn't enough. Manthan convenes a panel of expert personas, has each reason through your problem independently, then churns their answers into one stronger verdict.

  • Each expert, its best model — an engineer on Gemini, an ethicist on Claude, an economist on GPT. One conversation, many minds, each playing to its strength.
  • Blind first, then a real debate — every expert answers without seeing the others (no groupthink), then an optional round two where they read each other and revise or defend.
  • Synthesis that decides — a guide agent reads the whole panel and writes one decisive answer for you, surfacing disagreement only where it changes what you should do.
  • Local-first, your own keys — no accounts, no cloud; everything runs on your machine with every token and dollar tracked.
View on GitHub →
Multi-agentMulti-modelLocal-first
how the council churns
YouBriefone problem
ManyExperts answerblind · parallel
OneSynthesisthe verdict
↻ Debateoptional 2nd round
№ 05

CodeCrafter

2025 · shipped & adopted

An MCP server that drops AI straight into your codebase.

A "vibe coding" server with 15+ tools for file operations, code analysis, shell commands and project exploration — packaged as a one-click desktop extension that colleagues and senior devs actually adopted.

  • 20–50% less development time through AI-driven generation, debugging and documentation.
  • Syntax-aware editing and smart file operations, not blind text replacement.
  • Sandboxed execution with comprehensive error handling for secure AI workflows.
  • Shipped as a .dxt desktop extension — install in one click, no setup.
View on GitHub →
MCP serverNode.jsDesktop ext
impact
Dev time−20 to −50%
Tools15+
Adoptionteam-wide
Installone click
№ 06

Hierarchical Memory

2025 · open source

A structured, human-like memory that any agent can plug into.

An MCP server that swaps unstructured text dumps for a rigid four-level memory tree — so an agent files what it learns the way an engineer would.

  • Four levels — Core Identity, Projects, Tasks, and granular Micro-logs, all backed by SQLite.
  • Hybrid search — 60% semantic meaning blended with 40% keyword ranking, so it finds both exact facts and broad ideas.
  • Two-step retrieval — skim the summaries first, pull deep logs only when needed, and the context window never bloats.
  • Nothing forgotten by accident — full history is preserved.
View on GitHub →
MCP serverSQLiteHybrid search
retrieval · 60% semantic / 40% keyword
L1Core Identityfacts
L2Projectsscope
L3Taskswork
L4Micro-logssnippets
№ 07

CropConnect

2023 · Google Play

Connecting farmers to buyers — no middlemen.

An Android app that links farmers, consumers, transporters and traders directly, with an AI chatbot for farmer support. My early proof that I could ship something real, end to end.

  • Four user types with Firebase Auth and a real-time database backing it all.
  • Crop listing & management for farmers; state / city / type filtering for buyers.
  • An OpenAI-powered chatbot for farmer queries and support.
View on Google Play →
AndroidFirebaseOpenAI
shipped
PlatformGoogle Play
Users4 roles
BackendFirebase
№ 08

Memory MCP

2025 · open source

A lightweight semantic memory an agent can carry anywhere.

A different take on memory from Hierarchical — a featherweight MCP server giving agents a private, local semantic store. Local E5-small-v2 embeddings, a self-contained SQLite database, no cloud vectors.

  • Auto-tagged on the way in — it extracts categories and generates a 384-dim vector from each message's topic.
  • Multi-modal retrieval — cosine similarity for concepts, BM25 full-text for exact strings, plus tag filtering.
  • A deterministic NL time parser — "yesterday morning" or "first week of last month" become precise ISO boundaries.
  • Runs anywhere Node.js does — fully self-contained, zero external services.
View on GitHub →
MCP serverE5-small-v2SQLite
search · vector + BM25 + tags
EmbeddingsE5-small-v2
Vector384-dim
Retrievalcosine + BM25
TimeNL → ISO
№ 09

Understanding Anything

2026 · agent skill

Turns "explain this to me" into actually understanding it.

An open-source agent skill that reframes the model from a static textbook into a thinking coach — guiding active comprehension instead of handing over forgettable summaries.

  • Questions, not lectures — short, sharp, calibrated prompts that keep your critical thinking in the driver's seat.
  • Frameworks on tap — First Principles, Systems Thinking, Inversion, Socratic questioning, the Feynman Technique.
  • Builds your own mental models — it challenges assumptions to bridge passive knowledge and real, lasting mastery.
View on GitHub →
Agent skillLearningReasoning
frameworks it draws on
First Principles
Systems Thinking
Inversion
Socratic
Feynman Technique

A selection — the 20+ MCP servers, 30+ agents and 50+ pipelines didn't all make the list.

04 / Stack

What I reach for.

a.Agentic AI & Orchestration
AI harnessMulti-agent systemsLoop engineeringContext engineeringLong-horizon executionAutonomous reasoningAgent memorySub-agentsAgent coordinationAgent skillsTool orchestrationModel Context ProtocolNeoPilot
b.RAG & Retrieval
Advanced RAGMultimodal RAGGraph RAGHybrid searchChunking strategiesRe-rankingEmbedding modelsVector indexingChromaDBPineconeMilvuspgvectorFAISSE5-small-v2BM25
c.Knowledge Graphs
Neo4jGraph RAGCausal graphsOWL ontologyRDFDoc → graphRelationship mapping
d.Models & Evaluation
50+ LLMs evaluatedOpenAIAnthropic ClaudeGoogle GeminiDeepSeekGrokQwenKimiOpen-source LLMsFine-tuningPrompting techniquesPrompt cachingCost / token optimization
e.Voice, Vision & Multimodal
Realtime voice APIsTTS · STTWhisperOCRGoogle VisionTextractVision / PDF understandingDocument parsingMultimodal chat
f.Data & Analysis
AI-driven data analysisPattern detectionData visualizationExcel / CSV / PDF automationPandasNumPyspaCyStatistical analysis
g.Engineering & Platforms
PythonJavaScriptNode.jsFastAPIExpress.jsReact.jsDockerREST APIsGit / GitHubLinuxSQL · JavaMongoDBMySQLFirebaseAWS S3InfluxDB
h.Tools & Workflow
Claude CodeClaude DesktopCursorCodexOpenClawGraphXMCP serversAgent skills & pluginsBrowser automationLangChainN8NObsidian+ the frontier agent stack, daily
05 / Method

How I think about all this.

I keep coming back to one idea: a model is only as good as the system around it — what it remembers, how it reasons, and what it can actually carry out.

So I build for capability. Memory gives an agent a past; orchestration and a solid harness give it the reach to plan, use tools, and finish a long task. Get those right and intelligence starts to feel dependable.

06 / Beyond

The rest of the story.

Sharing what I know
  • Guest lectures · MES IMCC
    For MCA students —
    1. Graph Databases (Neo4j).
    2. Time Series Databases (InfluxDB).
    3. MongoDB.
    4. GenAI pipeline building.
  • Internal KSS sessions
    1. "Unlock AI" — the journey from next-token prediction to multi-agent systems.
    2. Claude Code: AI-Native Development.
    3. AI video creation.
    4. AI-assisted research.
    5. Prompt & context engineering.
Competitions
  • Winner · Idea X Ignition
    PCCOE, Pune.
  • Winner · Case Study
    Wadia College, Pune.
  • Runner-up · On-Spot Creativity
    IIMS, Pune.
On the field
  • Gold Medal · High Jump
    North Maharashtra University.
  • Division level
    Represented in Chess, High Jump and Judo.
Say hello

Let's make
something thoughtful.