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revanthpp/README.md

Hey there, I am Revanth

I build practical AI systems, workflows, and explainers that help people move from “this is interesting” to “wait, I can actually use this.”

My background spans software, analytics, data science, cloud, infrastructure, and AI. I started in Information Technology, moved into business analytics, worked on dashboards and data engineering workflows, then spent time in Azure cloud migration and infrastructure before moving deeper into AI, agentic systems, and applied automation.

So basically: I turn messy problems into systems that don’t collapse when real people touch them. Glamorous? Occasionally. Useful? Very.

What I’m focused on now

  • Building practical AI projects people can understand, reuse, and learn from
  • Exploring agentic systems, workflow automation, evaluations, and AI-assisted engineering
  • Turning AI concepts into simple explainers through FutureProofOS
  • Creating tools, templates, and demos that bridge the gap between AI hype and AI that actually helps
  • Writing about career growth, systems thinking, and how to stay useful in a fast-changing world

Featured work

I’m currently building and documenting projects around:

  • Agentic workflows
  • AI evaluation patterns
  • Practical automation
  • FutureProofOS
  • Second-brain systems for learning, career growth, and content creation

My style

I like building things that are:

  • Simple enough to explain
  • Useful enough to reuse
  • Clean enough to maintain
  • Practical enough to survive real users
  • Interesting enough that nobody falls asleep halfway through the README

Current learning areas

  • Agentic AI architecture
  • AI evaluation and observability
  • Prompt and context engineering
  • Workflow automation
  • Applied AI product thinking
  • Developer tools and AI-assisted coding

Connect with me

My GitHub goal

This profile is where I turn ideas into working experiments.

Some repos will be polished. Some will be learning-in-public. Some will probably start as “this should only take one weekend,” which is how all great side quests begin.

Either way, the goal is simple:

Build useful things. Explain them clearly. Help more people become future-proof.

Popular repositories Loading

  1. rev-astro-site rev-astro-site Public

    website for

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  2. evalkit evalkit Public

    Config-driven evaluation harness for LLM systems

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  3. agentops-simulator agentops-simulator Public

    Simulate AI workflow cost, routing, reliability, guardrails, and observability tradeoffs.

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  4. data-science-ipython-notebooks data-science-ipython-notebooks Public archive

    Forked from donnemartin/data-science-ipython-notebooks

    Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Pytho…

    Python

  5. pyeq2 pyeq2 Public archive

    Forked from zunzun/pyeq2

    A huge collection of equations for Python curve fitting and surface fitting that can output source code in several computing languages, and run a genetic algorithm for initial parameter estimation.…

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  6. Berkeley_Practical_Application-1 Berkeley_Practical_Application-1 Public archive

    Jupyter Notebook