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AWS adds seven objectives to the AI Practitioner exam guide five weeks after version 1.0
AWS published version 1.1 of the AIF-C01 AI Practitioner exam guide on April 30, five weeks after 1.0, with seven new objectives including token pricing. A dev.to review finds older courses still cover most of the exam but are thin on agents, token cost and grounding.
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What happened
- The guide says revisions reach the live exam about a month after publication, so version 1.1 content should appear around the end of May 2026.
- Agentic AI now appears in five objectives, among them a new 2.1.6 covering multi-agent patterns, Model Context Protocol, memory and tool use.
- Seven services joined the in-scope list, among them Amazon Bedrock AgentCore, Strands Agents and Kiro, while Amazon MemoryDB was removed.
- Model metrics objective 1.3.6 kept its number but dropped Area Under the Curve, and now lists accuracy, precision, recall and F1 score.
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Why it matters
- exposure Candidates who sit the exam after late May using a pre-revision question bank will practise examples AWS has retired, such as AUC, and will get no practice on the new agent and cost objectives.
- contradiction The revision table and the published objective disagree on Amazon Q, so AWS's own guide leaves candidates unable to tell whether the service is tested.
- precedent Two guide versions roughly five weeks apart mean prep material written against one version can go stale within weeks of being written.
Counting back five weeks from April 30 puts version 1.0 in late March 2026 [2]. The line-by-line comparison comes from a dev.to post whose author worked through AWS's revision page while writing practice questions [2]. According to that post, the revision makes two kinds of change. The first is new lines, seven of them: 1.2.6, 2.1.4, 2.1.5, 2.1.6, 3.2.5, 3.4.5 and 5.1.5 [6]. Alongside token pricing, they add the role of context engineering in foundation-model applications [7]. Others cover prompt versioning with Amazon Bedrock Prompt Management, business metrics such as cost per interaction, and hallucination detection and grounding [20]. One asks when to pick traditional ML over a foundation model, for reasons such as regulation or explainability [21].
The second kind keeps the objective number and changes the examples under it. "Some objectives kept their number but swapped their examples, which is where older question banks quietly go stale," the author wrote [12]. Objective 2.3.1 no longer cites Bedrock PartyRock or Bedrock Data Automation. Objective 3.1.6 asks candidates to define the role of AI agents without naming Amazon Bedrock Agents [14]. Inference types under 1.1.3 now include asynchronous and serverless, and 3.1.5 adds model distillation to the customization-cost list [15]. Objective 3.4.2 puts LLM-as-a-judge next to ROUGE, BLEU and BERTScore [15]. A diff tool keyed on objective IDs would report all of this as no change.
According to the post, agentic AI is the biggest change. Besides the new 2.1.6, it now sits in four existing objectives [9]. Those are the basic terms in 1.1.1, the comparison of AI, ML, GenAI and deep learning in 1.1.2, and real-world applications in 1.2.4 [9]. The fourth is security objective 5.1.1, through AgentCore Identity and Policy in AgentCore [9]. Objective 2.1.6 also covers multi-agent communication and workflow orchestration [8].
Objective 1.3.4 used to point at SageMaker Data Wrangler, Feature Store and Model Monitor [14]. Its published examples are now Amazon Bedrock, Amazon Quick, Kiro and SageMaker AI [11]. Amazon Quick and Amazon Q sitting a few lines apart will not help anyone skimming [10][11]. On the Amazon Q entry, the author wrote: "I would not spend much time on Amazon Q until the guide settles." [17]
The exam is 65 questions, 50 of them scored, and passing takes 700 of 1,000 [5]. That leaves 15 unscored [3]. Fundamentals of GenAI is weighted at 24 percent and Applications of Foundation Models at 28 [4]. Together that is 52 percent [4]. Five of the seven new lines carry the 2 and 3 prefixes that match those domains in the guide's ordering [5].
On this evidence, pre-May material needs a top-up. "If your course predates May 2026, keep it. Most of the exam is still the same material," the author wrote [18]. The suggested additions cover how agents work with MCP, memory and tools; how token counts shape cost, and the point at which RAG, fine-tuning or distillation becomes the cheaper choice; and Bedrock Guardrails, contextual grounding and Prompt Management [19]. I think the author's call is right for a team with a working course and an exam booked after the end of May [1]. The post does not count the unchanged objectives, so the share of the syllabus that moved cannot be calculated from it.
What to watch
- Whether AWS reconciles the Amazon Q entry, either by adding it to the in-scope page and objective 1.3.4 or by dropping it from the added-services list.
- Whether practice-exam banks retire AUC, PartyRock and Bedrock Agents items before version 1.1 content reaches the live exam around the end of May.
- A version 1.2 of the AIF-C01 guide; a third revision on a similar interval would show the syllabus moving at the pace of AWS product launches.