How conflicting agent responses hurt trust

One of the biggest challenges I see with scaling LLM agents isn’t the model itself. It’s context. Agents break down not because they “can’t think” but because they lose track of what’s happened, what’s been decided, and why. Here’s the pattern I notice: 👉 For short tasks, things work fine. The agent remembers the conversation so far, does its subtasks, and pulls everything together reliably. 👉 But the moment the task gets longer, the context window fills up, and the agent starts forgetting key decisions. That’s when results become inconsistent, and trust breaks down. That’s where Context Engineering comes in. 🔑 Principle 1: Share Full Context, Not Just Results Reliability starts with transparency. If an agent only shares the final outputs of subtasks, the decision-making trail is lost. That makes it impossible to debug or reproduce. You need the full trace, not just the answer. 🔑 Principle 2: Every Action Is an Implicit Decision Every step in a workflow isn’t just “doing the work”, it’s making a decision. And if those decisions conflict because context was lost along the way, you end up with unreliable results. ✨ The Solution to this is "Engineer Smarter Context" It’s not about dumping more history into the next step. It’s about carrying forward the right pieces of context: → Summarize the messy details into something digestible. → Keep the key decisions and turning points visible. → Drop the noise that doesn’t matter. When you do this well, agents can finally handle longer, more complex workflows without falling apart. Reliability doesn’t come from bigger context windows. It comes from smarter context windows. 〰️〰️〰️ Follow me (Aishwarya Srinivasan) for more AI insight and subscribe to my Substack to find more in-depth blogs and weekly updates in AI: https://lnkd.in/dpBNr6Jg

Agentic AI transformation is on the mind of every CEO I meet. But here’s what’s often missing from the conversation: when and how agents fail. And the truth is, they fail often. Microsoft’s AI Red Team notes that while many of these failures mirror those seen in LLMs, their frequency and impact are greatly amplified once agents operate with memory, tool access, and multi-agent collaboration . The whitepaper organizes failures into two groups: 𝗡𝗼𝘃𝗲𝗹 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗺𝗼𝗱𝗲𝘀 (𝘂𝗻𝗶𝗾𝘂𝗲 𝘁𝗼 𝗮𝗴𝗲𝗻𝘁𝘀): • Agent compromise or impersonation: attackers or even other agents pretending to be trusted components. • Multi-agent jailbreaks: one agent persuading another to ignore safeguards. • Flow manipulation and provisioning poisoning: poisoned configurations or orchestration logic redirect entire workflows. • Organizational knowledge loss: corrupted memories or over-delegation leading to long-term degradation of institutional knowledge. 𝗘𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗺𝗼𝗱𝗲𝘀 (𝗺𝗮𝗴𝗻𝗶𝗳𝗶𝗲𝗱 𝗯𝘆 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝘆): • Hallucinations: no longer just misleading text, but incorrect actions in enterprise systems. • Misinterpreted instructions: plausible but unintended workflows executed as if correct. • Bias amplification: skewed outputs scaling to affect whole populations of users. • Transparency and consent gaps: agents making consequential decisions without intelligible explanations. The paper stresses the effects of these failures: agent misalignment, action abuse, denial of service, incorrect decision-making, user harm, and erosion of trust . In practice, this means a poisoned memory entry can escalate into data exfiltration, or a misinterpreted instruction can lead to system-wide outages. Mitigation is possible and the taxonomy describes dozens of design controls. Distilling them, four stand out as foundational: 𝟭. 𝗜𝗱𝗲𝗻𝘁𝗶𝘁𝘆 𝗮𝗻𝗱 𝗽𝗲𝗿𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝗶𝗻𝗴: Each agent should have a unique identifier with role-based access. This makes impersonation harder and enables granular auditability. 𝟮. 𝗠𝗲𝗺𝗼𝗿𝘆 𝗵𝗮𝗿𝗱𝗲𝗻𝗶𝗻𝗴: Memory must be treated as an attack surface. That means authenticated writes, restricted reads, and live monitoring to detect poisoning or leakage. 𝟯. 𝗖𝗼𝗻𝘁𝗿𝗼𝗹-𝗳𝗹𝗼𝘄 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: Autonomy requires constraints. Critical tool calls and data accesses should be deterministically gated and verified to prevent cascading failures. 𝟰. 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗶𝘀𝗼𝗹𝗮𝘁𝗶𝗼𝗻: Agents should operate in strong sandboxes so that a compromised or malfunctioning component cannot propagate failures beyond its scope. Agentic AI doesn’t just inherit old risks, it introduces new ones that are harder to anticipate and more damaging when they occur. Transformation without failure-mode awareness isn’t transformation at all. It’s exposure. Enterprises that succeed will be those that invest as much in designing for failure as in scaling capability.

“You were slow in this task” vs “You’re just a slow person” 😭😭😭😭 That one shift taught me a powerful leadership lesson. A few months ago, I gave feedback to a team member about missing a deadline. I thought I was being clear and objective. But later, they pulled me aside and said, “I felt like you weren’t just frustrated with the work , I felt like you were frustrated with me.”😭😭😭😭😭 That moment hit hard. I realized I’d blurred the line between task conflict and person conflict. And in doing so, I had unknowingly made someone feel personally attacked rather than professionally challenged. ✅ Task conflict is healthy — it’s when we disagree about the how, the what, the when. ❌ Person conflict is damaging It questions who someone is.And not what they did . Its real dislike which may arise from personality clashes And that’s the difference between task conflict and person conflict. 🧠 Task Conflict is healthy: “I don’t agree with this strategy — can we rethink it?” “I think the data needs more context.” “We’re not aligned on timelines — let’s review them.” 🎯 It’s about the work. It’s forward-looking. It sharpens thinking. 🔥 Person Conflict is harmful: “You never think things through.” “You’re too slow for this role.” “You’re always difficult in meetings.” 😓 It’s about the person. It creates shame. It shuts people down. The traps many managers fall into: Turning patterns into labels (“You always do this”) Giving feedback in the heat of the moment Using words like :you are" instead of "this was" Confusing directness with bluntness Forgetting that tone travels faster than logic Since that conversation, I’ve made it a personal leadership practice to: Separate feedback from identity Stay curious, not critical Challenge ideas not people 💡 Conflict isn’t bad. It’s unskilled conflict that breaks trust. The goal isn’t to avoid tension it’s to handle it with wisdom. Winfield Strategy & Innovation - Winfield Business School #Leadership #FeedbackCulture #EmotionalIntelligence #TeamDevelopment #ConflictResolution

ESG ratings are supposed to help investors make informed decisions about a company’s sustainability performance, but what happens when different rating agencies give completely different scores? This inconsistency creates confusion in the market, making it harder for investors to trust ESG evaluations. But more importantly, it puts companies in a tricky spot—do they address the uncertainty head-on, or do they try to shape the narrative in their favor? One of the most interesting aspects of this issue is how ESG rating disagreements can actually impact stock prices. When investors are unsure about a company’s real ESG performance, they might lose confidence, leading to stock price volatility or, in extreme cases, a crash. And that’s where this study comes in. Hua Chen and Zhuang Wang, in their research “Does ESG Rating Disagreement Affect Management Tone Manipulation?”, explore whether companies tweak the way they communicate—specifically by using more positive language—to manage investor perceptions when their ESG ratings don’t align. What They Found: - Companies facing large ESG rating differences tend to manipulate their tone, making their reports sound more optimistic to offset investor uncertainty. - The more pressure companies feel from investors, the more they adjust their messaging to maintain trust. -Conflicting ESG scores create “noise,” giving companies an opportunity to craft a more favorable image even if their ESG performance isn’t strong. -This kind of tone manipulation, over time, can increase the risk of stock price crashes, because investors eventually catch on to the mismatch between words and reality. This study raises an important point: if ESG ratings aren’t standardized, not only does it make life harder for investors, but it also gives companies more room to spin their sustainability story. It’s a reminder that while ESG disclosure is important, how companies communicate ESG matters just as much as the numbers themselves. You can find the full report below. Ramadan Mubarak to all! #ESG #StockPrice https://lnkd.in/dxy9j_9F