Retrieve before you reason
Start with chunking, indexing, query design, and observable retrieval. Agency cannot rescue missing evidence.
From first retrieval to evaluated agent
Stop reading in circles.
Build your RAG route.
Choose where you are, what you need to ship, and the hours you actually have. Get a sequenced Agentic RAG curriculum you can finish, track, and take with you.
Your route
Make the complete journey yours.
The path changes with your starting point and intended outcome. Every route includes a working capstone and a way to test whether it deserves trust.
Evaluation route
A reliable agent,
from the ground up.
10estimated weeks
0 of 6 stages complete40 focused hours
The whole system
RAG is a pipeline before it is an agent.
Each stage adds one capability and one check. The goal is not more machinery. It is evidence that the machinery improves the answer.
Measure the evidence
Track recall, ranking quality, groundedness, and task success separately. One score hides where the system broke.
Give tools narrow contracts
Define inputs, outputs, failure states, and stopping rules before an agent can call a tool.
Keep a trace
A useful agent leaves enough state to replay why it searched, selected, retried, or stopped.
Earn complexity
Add routing, memory, and loops only after the simpler retrieval baseline has a measured limit.
What mastery means
From answer to evidence.
A polished response is not the finish line. A complete Agentic RAG practice can explain what it retrieved, why the agent acted, and how the result was tested.
Build a small labeled query set. Inspect misses by source, chunk boundary, vocabulary, and rank before changing the generator.
Require claim-level evidence, test abstention, and separate faithful use of context from fluent phrasing.
Compare the agent with a non-agentic baseline. Count tool calls, loops, latency, failures, and resolved tasks.
Persist traces, retrieved passages, tool inputs, decisions, and termination reasons so improvement starts from evidence.
Your first good agent starts with a smaller next step.
Generate the route, finish one deliverable, and keep the roadmap beside the code.
Build my Agentic RAG pathAgentic RAG Curriculum Architecture & Schedule Mechanics
How does Agentic RAG Pathfinder calculate total curriculum hours and calendar duration across experience tiers and outcomes?
Agentic RAG Pathfinder computes study plans by combining four core retrieval-augmented generation modules with track-specific capstone units. The client-side script adjusts module workloads based on experience level: 'beginner' retains full duration, 'builder' discounts early units by two hours with a three-hour floor, and 'advanced' drops the introductory module entirely. The interface then divides the resulting workload by weekly allocated study hours and applies ceiling arithmetic to establish estimated calendar duration.
Pacing estimates assume constant weekly study velocity and pre-calibrated module hour weights. They represent instructional planning heuristics rather than formal accreditation, empirical completion benchmarks, or guaranteed engineering proficiency.
Try a worked example
Select 'Builder' under Current experience, choose 'Prototype' under Primary outcome, enter 5 in the weekly hours field, and click 'Generate path'. The script adapts the four core stages (RAG foundations drops from 6h to 4h, Retrieval drops from 8h to 6h, while Grounded generation and Agency remain 6h and 8h) and attaches two prototype modules (Useful interaction loop at 5h, Working prototype at 5h). This yields 34 total focused hours; dividing by 5 hours per week with ceiling rounding yields an estimated 7 weeks.
Workload Slicing and Pacing Arithmetic
The planner maintains four baseline stages (Foundations, Retrieval, Grounded generation, Agent loop) totaling 28 hours. Outcome selection introduces two goal-specific stages: Evaluation adds 12h, Prototype adds 10h, Production adds 16h, and Research adds 16h. When Advanced is selected, the first baseline module is removed (stages.slice(1)) and remaining early modules are discounted, recalculating calendar completion via Math.ceil(total / hours).
State is serialized under the local storage key 'agentic-rag-pathfinder-v1'. Toggling stage completion updates the in-memory completed identifiers array and dynamically computes the progress bar width percentage relative to active curriculum length.
A local roadmap converts fixed workloads into calendar estimates
Read the explanation
The beginner evaluation route combines four foundation stages and two goal-specific stages: six, eight, six, eight, seven and five hours, totaling forty. Builder experience reduces the first two by two hours each, producing thirty-six. The curriculum is locally authored fixed material, not generated from research or a model call. Each stage includes a suggested proof check rather than proof that the visitor completed it. Advanced mode removes the foundation stage and subtracts two hours from each remaining stage with a three-hour minimum. For evaluation, the five stages total twenty-four hours. At four hours per week the estimate is six weeks, versus ten for the beginner. These are workload estimates, not deadlines or guaranteed mastery. Weekly hours must be between one and forty. Calendar time uses the ceiling of total hours divided by weekly hours. Forty hours at six per week therefore shows seven weeks. Marking a stage changes local progress, not an automatic assessment. Changing experience or goal clears checkmarks. Reset restores beginner evaluation with four hours a week. Download exports the current roadmap, proof suggestions and manual progress as Markdown. No paper content, live benchmark or deployed agent is verified.