AI & Product Engineering, Explained
Plain-English definitions for the terms we use every day — no jargon left unexplained.
Agentic AI
Agentic AI refers to autonomous systems capable of executing multi-step goals without requiring humans to prompt each individual decision. Unlike simple text-generation bots that respond to isolated queries, agentic workflows reason through objectives, call external APIs, query databases, evaluate intermediate outcomes, and adapt their next steps dynamically to accomplish complex tasks from start to finish.
An autonomous agent that inspects an incoming sales lead, browses their LinkedIn profile, drafts a tailored proposal, and schedules a meeting on your calendar.
AI SDR
An AI SDR (Sales Development Representative) is an autonomous software agent designed to handle the time-intensive outbound sales cycle. It prospect-matches target accounts, analyzes public activity to extract personalized pain points, crafts tailored first-touch messages, and coordinates initial conversation replies — achieving human-grade personalization at machine speed without increasing headcount.
SolveEase’s Fleets platform research pipeline, which achieves 20–30% reply rates across targeted B2B campaigns.
Context Window
A context window is the maximum volume of text tokens an LLM can process, read, and maintain in memory during a single interaction. It bounds how much conversation history, external documentation, or background information the model can evaluate simultaneously before earlier context is discarded or summarized.
Passing an entire 150-page technical specification into Claude or Gemini so it can answer architectural questions across all chapters.
Embeddings
Embeddings are dense mathematical representations (vectors of numbers) of text, audio, or images that encode conceptual meaning rather than raw words. By translating sentences into points in a high-dimensional mathematical space, machine learning systems can calculate semantic proximity — allowing algorithms to recognize that "budget hotel" and "cheap accommodation" represent near-identical user intents.
Converting real estate descriptions into 1536-dimensional vectors to recommend properties that match the buyer’s aesthetic preferences.
Fine-Tuning
Fine-tuning is the process of taking an existing foundation model (such as Llama, Mistral, or GPT) and performing additional supervised training on a curated, domain-specific dataset. This adjusts the model’s internal weights, instilling specialized domain vocabulary, strict styling constraints, or proprietary reasoning patterns without the cost of training a model from scratch.
Training an open-source model on proprietary medical diagnosis guidelines or specialized legal contract terminology.
LLM (Large Language Model)
Large Language Models are neural network architectures (typically based on the Transformer architecture) trained on vast corpuses of text to predict and generate natural human language. Models like GPT-4, Claude 3.5, and Gemini power modern conversational interfaces, code synthesis, summarization pipelines, and natural-language workflow engines.
Using an LLM backend to automatically generate compelling property listing descriptions for real estate platforms like BuyNoida.
MVP (Minimum Viable Product)
A Minimum Viable Product is the most focused, functional version of a software product that delivers real core value to real users. An MVP avoids secondary features to launch rapidly (typically 4–8 weeks), validating genuine market demand, testing monetization assumptions, and gathering real user usage data before investing capital in a broader build.
Launching QIXR in 6 weeks with core booking and payments to validate home-service market demand before adding complex enterprise features.
PWA (Progressive Web App)
Progressive Web Applications are web applications built with modern browser APIs (such as service workers and web app manifests) that deliver an installable, mobile-app-like experience directly from the web browser. They provide offline caching, push notifications, and fast loading speeds without requiring App Store approvals or 30% developer revenue cuts.
Delivering mobile-responsive dashboards for field service workers that work smoothly in weak connectivity environments.
RAG (Retrieval-Augmented Generation)
Retrieval-Augmented Generation is an architecture that links an LLM to an external knowledge source. When a user asks a question, the system searches your private company documents for the most relevant facts, feeds them to the model alongside the question, and instructs the model to answer based strictly on those retrieved facts — dramatically reducing hallucinations and grounding answers in real truth.
An internal documentation assistant that answers employee questions by quoting exact passages from private company SOPs and policies.
Vector Search
Vector search is a database querying technique that retrieves records based on conceptual similarity rather than exact keyword matching. Using specialized vector databases (such as pgvector, Pinecone, or Qdrant), queries are converted into mathematical embeddings and matched against stored data by computing cosine distance, surfacing relevant answers even when searchers use completely different phrasing.
Searching a catalog of 10,000 legal documents for "unauthorized data sharing" and instantly returning clauses labeled "third-party disclosure restrictions".
Workflow Automation
Workflow automation refers to software infrastructure that eliminates repetitive manual business processes across multiple disconnected tools. Modern AI-assisted automation connects CRMs, WhatsApp APIs, databases, payment gateways, and accounting tools into deterministic execution pipelines that trigger actions, sync records, and send notifications autonomously.
SolveEase WB and WhatsApp integrations that qualify incoming leads, update database records, issue invoices, and notify account executives automatically.
Zero-Knowledge Proofs (ZK-Proofs)
A Zero-Knowledge Proof is a cryptographic technique that enables one party to prove to another that a statement is mathematically true, without revealing any additional secret information beyond the statement’s validity. This allows verification of identity, credentials, or balances while keeping the underlying sensitive data completely confidential.
Our award-winning AutoDoc system at IIT Kharagpur, verifying authentic university degrees on-chain without exposing student private transcripts.
See these concepts applied to a real product
Check our production case studies or book a scoping call with our founders.